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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2405.20978 | Felton Fang | Feiteng Fang, Yuelin Bai, Shiwen Ni, Min Yang, Xiaojun Chen and
Ruifeng Xu | Enhancing Noise Robustness of Retrieval-Augmented Language Models with
Adaptive Adversarial Training | null | ACL 2024, Main Conference | null | null | cs.AI | http://creativecommons.org/licenses/by/4.0/ | Large Language Models (LLMs) exhibit substantial capabilities yet encounter
challenges, including hallucination, outdated knowledge, and untraceable
reasoning processes. Retrieval-augmented generation (RAG) has emerged as a
promising solution, integrating knowledge from external databases to mitigate
these challenges... | [
{
"created": "Fri, 31 May 2024 16:24:53 GMT",
"version": "v1"
}
] | 2024-06-03 | [
[
"Fang",
"Feiteng",
""
],
[
"Bai",
"Yuelin",
""
],
[
"Ni",
"Shiwen",
""
],
[
"Yang",
"Min",
""
],
[
"Chen",
"Xiaojun",
""
],
[
"Xu",
"Ruifeng",
""
]
] |
2405.20980 | Felix Mujkanovic | Felix Mujkanovic, Ntumba Elie Nsampi, Christian Theobalt, Hans-Peter
Seidel, Thomas Leimk\"uhler | Neural Gaussian Scale-Space Fields | 15 pages; SIGGRAPH 2024; project page at
https://neural-gaussian-scale-space-fields.mpi-inf.mpg.de | ACM Transactions on Graphics, Volume 43, Issue 4, July 2024 | 10.1145/3658163 | null | cs.CV cs.GR cs.LG | http://creativecommons.org/licenses/by/4.0/ | Gaussian scale spaces are a cornerstone of signal representation and
processing, with applications in filtering, multiscale analysis, anti-aliasing,
and many more. However, obtaining such a scale space is costly and cumbersome,
in particular for continuous representations such as neural fields. We present
an efficien... | [
{
"created": "Fri, 31 May 2024 16:26:08 GMT",
"version": "v1"
}
] | 2024-07-23 | [
[
"Mujkanovic",
"Felix",
""
],
[
"Nsampi",
"Ntumba Elie",
""
],
[
"Theobalt",
"Christian",
""
],
[
"Seidel",
"Hans-Peter",
""
],
[
"Leimkühler",
"Thomas",
""
]
] |
2405.21003 | Amr Alkhatib | Amr Alkhatib, Henrik Bostr\"om, Michalis Vazirgiannis | Explaining Predictions by Characteristic Rules | Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2022 | In: Machine Learning and Knowledge Discovery in Databases. ECML
PKDD 2022. Lecture Notes in Computer Science(), vol 13713. Springer, Cham
(2023) | 10.1007/978-3-031-26387-3_24 | null | cs.LG cs.AI | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Characteristic rules have been advocated for their ability to improve
interpretability over discriminative rules within the area of rule learning.
However, the former type of rule has not yet been used by techniques for
explaining predictions. A novel explanation technique, called CEGA
(Characteristic Explanatory Gen... | [
{
"created": "Fri, 31 May 2024 16:44:40 GMT",
"version": "v1"
}
] | 2024-06-03 | [
[
"Alkhatib",
"Amr",
""
],
[
"Boström",
"Henrik",
""
],
[
"Vazirgiannis",
"Michalis",
""
]
] |
2405.21043 | Fengdi Che | Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A
Ramirez, Christopher K Harris, A. Rupam Mahmood, Dale Schuurmans | Target Networks and Over-parameterization Stabilize Off-policy
Bootstrapping with Function Approximation | null | Proceedings of the 41 st International Conference on Machine
Learning, 2024 | null | null | cs.LG cs.AI | http://creativecommons.org/licenses/by-nc-nd/4.0/ | We prove that the combination of a target network and over-parameterized
linear function approximation establishes a weaker convergence condition for
bootstrapped value estimation in certain cases, even with off-policy data. Our
condition is naturally satisfied for expected updates over the entire
state-action space ... | [
{
"created": "Fri, 31 May 2024 17:36:16 GMT",
"version": "v1"
},
{
"created": "Fri, 4 Oct 2024 18:04:33 GMT",
"version": "v2"
}
] | 2024-10-08 | [
[
"Che",
"Fengdi",
""
],
[
"Xiao",
"Chenjun",
""
],
[
"Mei",
"Jincheng",
""
],
[
"Dai",
"Bo",
""
],
[
"Gummadi",
"Ramki",
""
],
[
"Ramirez",
"Oscar A",
""
],
[
"Harris",
"Christopher K",
""
],
[
"Mahm... |
2406.00123 | Mingyuan Meng | Mingyuan Meng, Dagan Feng, Lei Bi, and Jinman Kim | Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image
Registration | Accepted at CVPR2024 as Oral Presentation && Best Paper Candidate | Proceedings of the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), 2024, pp. 9645-9654 | null | null | eess.IV cs.CV | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Deformable image registration is a fundamental step for medical image
analysis. Recently, transformers have been used for registration and
outperformed Convolutional Neural Networks (CNNs). Transformers can capture
long-range dependence among image features, which have been shown beneficial
for registration. However,... | [
{
"created": "Fri, 31 May 2024 18:25:23 GMT",
"version": "v1"
},
{
"created": "Wed, 12 Jun 2024 12:21:52 GMT",
"version": "v2"
}
] | 2024-06-13 | [
[
"Meng",
"Mingyuan",
""
],
[
"Feng",
"Dagan",
""
],
[
"Bi",
"Lei",
""
],
[
"Kim",
"Jinman",
""
]
] |
2406.00291 | Yiyang Zhao | Yiyang Zhao, Linnan Wang, Tian Guo | Multi-Objective Neural Architecture Search by Learning Search Space
Partitions | null | Journal of Machine Learning Research 25 (2024) 1-41 | null | null | cs.LG cs.AI | http://creativecommons.org/licenses/by/4.0/ | Deploying deep learning models requires taking into consideration neural
network metrics such as model size, inference latency, and #FLOPs, aside from
inference accuracy. This results in deep learning model designers leveraging
multi-objective optimization to design effective deep neural networks in
multiple criteria... | [
{
"created": "Sat, 1 Jun 2024 03:51:34 GMT",
"version": "v1"
},
{
"created": "Thu, 18 Jul 2024 01:53:35 GMT",
"version": "v2"
}
] | 2024-08-20 | [
[
"Zhao",
"Yiyang",
""
],
[
"Wang",
"Linnan",
""
],
[
"Guo",
"Tian",
""
]
] |
2406.00423 | Luis Rei | Luis Rei and Dunja Mladeni\'c and Mareike Dorozynski and Franz
Rottensteiner and Thomas Schleider and Rapha\"el Troncy and Jorge Sebasti\'an
Lozano and Mar Gait\'an Salvatella | Multimodal Metadata Assignment for Cultural Heritage Artifacts | null | Multimedia Systems 29 (2023) 847-869 | 10.1007/s00530-022-01025-2 | null | cs.CV cs.LG | http://creativecommons.org/licenses/by/4.0/ | We develop a multimodal classifier for the cultural heritage domain using a
late fusion approach and introduce a novel dataset. The three modalities are
Image, Text, and Tabular data. We based the image classifier on a ResNet
convolutional neural network architecture and the text classifier on a
multilingual transfor... | [
{
"created": "Sat, 1 Jun 2024 12:41:03 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Rei",
"Luis",
""
],
[
"Mladenić",
"Dunja",
""
],
[
"Dorozynski",
"Mareike",
""
],
[
"Rottensteiner",
"Franz",
""
],
[
"Schleider",
"Thomas",
""
],
[
"Troncy",
"Raphaël",
""
],
[
"Lozano",
"Jorge Sebastián",
... |
2406.00512 | Marcos Faundez-Zanuy | Marcos Faundez-Zanuy, Moises Diaz | On the use of first and second derivative approximations for biometric
online signature recognition | Advances in Computational Intelligence. IWANN 2023. pp 461 to 472 | Lecture Notes in Computer Science, vol 14134, 2023 | 10.1007/978-3-031-43085-5_36 | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | This paper investigates the impact of different approximation methods in
feature extraction for pattern recognition applications, specifically focused
on delta and delta-delta parameters. Using MCYT330 online signature data-base,
our experiments show that 11-point approximation outperforms 1-point
approximation, resu... | [
{
"created": "Sat, 1 Jun 2024 17:36:34 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Faundez-Zanuy",
"Marcos",
""
],
[
"Diaz",
"Moises",
""
]
] |
2406.00848 | Hamza El Housni | Abdelilah Nossair, Hamza El Housni | Eating Smart: Advancing Health Informatics with the Grounding DINO based
Dietary Assistant App | The work presented in this paper was part of the proceedings for the
First International Conference on Artificial Intelligence (ICATA 2024) | Eating Smart: Advancing Health Informatics with the Grounding
DINO-based Dietary Assistant App, International Journal of Scientific and
Innovative Studies, June 2024, Volume 3, Number 3, Pages 26-34, Available
online at IJSRIS | 10.5281/zenodo.11243881 | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | The Smart Dietary Assistant utilizes Machine Learning to provide personalized
dietary advice, focusing on users with conditions like diabetes. This app
leverages the Grounding DINO model, which combines a text encoder and image
backbone to enhance food item detection without requiring a labeled dataset.
With an AP sc... | [
{
"created": "Sun, 2 Jun 2024 19:59:07 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Nossair",
"Abdelilah",
""
],
[
"Housni",
"Hamza El",
""
]
] |
2406.01026 | Xue Mengge | Mengge Xue, Zhenyu Hu, Liqun Liu, Kuo Liao, Shuang Li, Honglin Han,
Meng Zhao, Chengguo Yin | Strengthened Symbol Binding Makes Large Language Models Reliable
Multiple-Choice Selectors | Accept at ACL2024 Main | ACL 2024 | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Multiple-Choice Questions (MCQs) constitute a critical area of research in
the study of Large Language Models (LLMs). Previous works have investigated the
selection bias problem in MCQs within few-shot scenarios, in which the LLM's
performance may be influenced by the presentation of answer choices, leaving
the selec... | [
{
"created": "Mon, 3 Jun 2024 06:20:12 GMT",
"version": "v1"
},
{
"created": "Thu, 6 Jun 2024 06:32:45 GMT",
"version": "v2"
}
] | 2024-06-07 | [
[
"Xue",
"Mengge",
""
],
[
"Hu",
"Zhenyu",
""
],
[
"Liu",
"Liqun",
""
],
[
"Liao",
"Kuo",
""
],
[
"Li",
"Shuang",
""
],
[
"Han",
"Honglin",
""
],
[
"Zhao",
"Meng",
""
],
[
"Yin",
"Chengguo",
"... |
2406.01062 | Qilong Zhangli | Qilong Zhangli, Jindong Jiang, Di Liu, Licheng Yu, Xiaoliang Dai,
Ankit Ramchandani, Guan Pang, Dimitris N. Metaxas, Praveen Krishnan | Layout Agnostic Scene Text Image Synthesis with Diffusion Models | Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern
Recognition (CVPR), 2024, pp. 7496-7506 | Proceedings of the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), 2024, pp. 7496-7506 | null | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | While diffusion models have significantly advanced the quality of image
generation their capability to accurately and coherently render text within
these images remains a substantial challenge. Conventional diffusion-based
methods for scene text generation are typically limited by their reliance on an
intermediate la... | [
{
"created": "Mon, 3 Jun 2024 07:20:34 GMT",
"version": "v1"
},
{
"created": "Tue, 11 Jun 2024 01:17:02 GMT",
"version": "v2"
},
{
"created": "Mon, 8 Jul 2024 02:10:06 GMT",
"version": "v3"
},
{
"created": "Fri, 19 Jul 2024 19:22:24 GMT",
"version": "v4"
},
{
"cre... | 2024-09-17 | [
[
"Zhangli",
"Qilong",
""
],
[
"Jiang",
"Jindong",
""
],
[
"Liu",
"Di",
""
],
[
"Yu",
"Licheng",
""
],
[
"Dai",
"Xiaoliang",
""
],
[
"Ramchandani",
"Ankit",
""
],
[
"Pang",
"Guan",
""
],
[
"Metaxas",
... |
2406.01096 | Anjanava Biswas | Wrick Talukdar, Anjanava Biswas | Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for
Accurate Natural Language Task Modeling | null | International Journal of Innovative Science and Research
Technology: Vol. 9 (2024): No. 5, 1499-1508 | 10.38124/ijisrt/IJISRT24MAY2087 | null | cs.CL cs.LG | http://creativecommons.org/licenses/by-nc-nd/4.0/ | While supervised learning models have shown remarkable performance in various
natural language processing (NLP) tasks, their success heavily relies on the
availability of large-scale labeled datasets, which can be costly and
time-consuming to obtain. Conversely, unsupervised learning techniques can
leverage abundant ... | [
{
"created": "Mon, 3 Jun 2024 08:31:35 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Talukdar",
"Wrick",
""
],
[
"Biswas",
"Anjanava",
""
]
] |
2406.01233 | Viktor Scherbakov | Viktor Shcherbakov, Fedor Krasnov | Multi-word Term Embeddings Improve Lexical Product Retrieval | 10 pages, 4 figures | In Proceedings of the Seventh Workshop on e-Commerce and NLP,
LREC-COLING 2024, pages 115-124, Torino, Italia. ELRA and ICCL | null | null | cs.IR cs.CL | http://creativecommons.org/licenses/by/4.0/ | Product search is uniquely different from search for documents, Internet
resources or vacancies, therefore it requires the development of specialized
search systems. The present work describes the H1 embdedding model, designed
for an offline term indexing of product descriptions at e-commerce platforms.
The model is ... | [
{
"created": "Mon, 3 Jun 2024 11:52:52 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Shcherbakov",
"Viktor",
""
],
[
"Krasnov",
"Fedor",
""
]
] |
2406.01377 | Weihao Zeng | Weihao Zeng, Joseph Campbell, Simon Stepputtis, Katia Sycara | Multi-Agent Transfer Learning via Temporal Contrastive Learning | 6 pages, 6 figures | 2024 IEEE International Conference on Robotics and Automation
(ICRA) 2024 | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper introduces a novel transfer learning framework for deep
multi-agent reinforcement learning. The approach automatically combines
goal-conditioned policies with temporal contrastive learning to discover
meaningful sub-goals. The approach involves pre-training a goal-conditioned
agent, finetuning it on the ta... | [
{
"created": "Mon, 3 Jun 2024 14:42:14 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Zeng",
"Weihao",
""
],
[
"Campbell",
"Joseph",
""
],
[
"Stepputtis",
"Simon",
""
],
[
"Sycara",
"Katia",
""
]
] |
2406.01421 | Zihao Zhang | Phillip Fernberg, Zihao Zhang | Problematizing AI Omnipresence in Landscape Architecture | null | Journal of Digital Landscape Architecture, 2024 | 10.14627/537752069 | null | cs.AI cs.LG | http://creativecommons.org/licenses/by-nc-nd/4.0/ | This position paper argues for, and offers, a critical lens through which to
examine the current AI frenzy in the landscape architecture profession. In it,
the authors propose five archetypes or mental modes that landscape architects
might inhabit when thinking about AI. Rather than limiting judgments of AI use
to a ... | [
{
"created": "Mon, 3 Jun 2024 15:20:05 GMT",
"version": "v1"
}
] | 2024-06-04 | [
[
"Fernberg",
"Phillip",
""
],
[
"Zhang",
"Zihao",
""
]
] |
2406.01618 | Anjanava Biswas | Anjanava Biswas, Wrick Talukdar | FinEmbedDiff: A Cost-Effective Approach of Classifying Financial
Documents with Vector Sampling using Multi-modal Embedding Models | 10 pages, 3 figures | International Research Journal of Modernization in Engineering
Technology and Science: Vol. 06 (2024): No. 5, 6142-6152 | 10.56726/IRJMETS57269 | null | cs.IR cs.AI | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Accurate classification of multi-modal financial documents, containing text,
tables, charts, and images, is crucial but challenging. Traditional text-based
approaches often fail to capture the complex multi-modal nature of these
documents. We propose FinEmbedDiff, a cost-effective vector sampling method
that leverage... | [
{
"created": "Tue, 28 May 2024 16:34:24 GMT",
"version": "v1"
}
] | 2024-06-05 | [
[
"Biswas",
"Anjanava",
""
],
[
"Talukdar",
"Wrick",
""
]
] |
2406.01624 | Alaa Nfissi | Alaa Nfissi, Wassim Bouachir, Nizar Bouguila, Brian Mishara | Unveiling Hidden Factors: Explainable AI for Feature Boosting in Speech
Emotion Recognition | Published in: Springer Nature International Journal of Applied
Intelligence (2024) | Applied Intelligence (2024), 1-24 | 10.1007/s10489-024-05536-5 | null | eess.AS cs.AI cs.CL cs.LG cs.SD | http://creativecommons.org/licenses/by/4.0/ | Speech emotion recognition (SER) has gained significant attention due to its
several application fields, such as mental health, education, and
human-computer interaction. However, the accuracy of SER systems is hindered by
high-dimensional feature sets that may contain irrelevant and redundant
information. To overcom... | [
{
"created": "Sat, 1 Jun 2024 00:39:55 GMT",
"version": "v1"
},
{
"created": "Wed, 5 Jun 2024 22:21:55 GMT",
"version": "v2"
}
] | 2024-06-07 | [
[
"Nfissi",
"Alaa",
""
],
[
"Bouachir",
"Wassim",
""
],
[
"Bouguila",
"Nizar",
""
],
[
"Mishara",
"Brian",
""
]
] |
2406.01782 | Leopoldo Carlos Agorio Grove | Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana, Santiago
Paternain, Juan Andres Bazerque | Multi-agent assignment via state augmented reinforcement learning | 12 pages, 3 figures, 6th Annual Conference on Learning for Dynamics
and Control | Proceedings of Machine Learning Research vol 242 1 12, 2024. 6th
Annual Conference on Learning for Dynamics and Control | null | null | eess.SY cs.AI cs.LG cs.MA cs.SY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We address the conflicting requirements of a multi-agent assignment problem
through constrained reinforcement learning, emphasizing the inadequacy of
standard regularization techniques for this purpose. Instead, we recur to a
state augmentation approach in which the oscillation of dual variables is
exploited by agent... | [
{
"created": "Mon, 3 Jun 2024 20:56:12 GMT",
"version": "v1"
}
] | 2024-06-05 | [
[
"Agorio",
"Leopoldo",
""
],
[
"Van Alen",
"Sean",
""
],
[
"Calvo-Fullana",
"Miguel",
""
],
[
"Paternain",
"Santiago",
""
],
[
"Bazerque",
"Juan Andres",
""
]
] |
2406.01789 | Mario Truss | Mario Truss, Stephan Boehm | AI-based Classification of Customer Support Tickets: State of the Art
and Implementation with AutoML | null | Proceedings of the IWEMB 2021/2022: Fifth and Sixth International
Workshop on Entrepreneurship, Electronic and Mobile Business | null | null | cs.LG cs.AI cs.CL cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Automation of support ticket classification is crucial to improve customer
support performance and shortening resolution time for customer inquiries. This
research aims to test the applicability of automated machine learning (AutoML)
as a technology to train a machine learning model (ML model) that can classify
suppo... | [
{
"created": "Mon, 3 Jun 2024 21:13:02 GMT",
"version": "v1"
}
] | 2024-06-05 | [
[
"Truss",
"Mario",
""
],
[
"Boehm",
"Stephan",
""
]
] |
2406.01956 | Panfeng Li | Zhicheng Ding, Panfeng Li, Qikai Yang, Siyang Li | Enhance Image-to-Image Generation with LLaVA-generated Prompts | Accepted by 2024 5th International Conference on Information Science,
Parallel and Distributed Systems | Proceedings of the 2024 5th International Conference on
Information Science, Parallel and Distributed Systems (ISPDS), 2024, pp.
77-81 | 10.1109/ISPDS62779.2024.10667513 | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | This paper presents a novel approach to enhance image-to-image generation by
leveraging the multimodal capabilities of the Large Language and Vision
Assistant (LLaVA). We propose a framework where LLaVA analyzes input images and
generates textual descriptions, hereinafter LLaVA-generated prompts. These
prompts, along... | [
{
"created": "Tue, 4 Jun 2024 04:31:39 GMT",
"version": "v1"
},
{
"created": "Fri, 20 Sep 2024 23:03:49 GMT",
"version": "v2"
}
] | 2024-09-24 | [
[
"Ding",
"Zhicheng",
""
],
[
"Li",
"Panfeng",
""
],
[
"Yang",
"Qikai",
""
],
[
"Li",
"Siyang",
""
]
] |
2406.02018 | Manasi Sharma | Manasi Sharma, Ho Chit Siu, Rohan Paleja, Jaime D. Pe\~na | Why Would You Suggest That? Human Trust in Language Model Responses | null | ICML Humans, Algorithmic Decision-Making and Society: Modeling
Interactions and Impact Workshop 2024 | null | null | cs.CL cs.AI cs.HC | http://creativecommons.org/licenses/by/4.0/ | The emergence of Large Language Models (LLMs) has revealed a growing need for
human-AI collaboration, especially in creative decision-making scenarios where
trust and reliance are paramount. Through human studies and model evaluations
on the open-ended News Headline Generation task from the LaMP benchmark, we
analyze... | [
{
"created": "Tue, 4 Jun 2024 06:57:47 GMT",
"version": "v1"
},
{
"created": "Fri, 4 Oct 2024 16:46:00 GMT",
"version": "v2"
}
] | 2024-10-07 | [
[
"Sharma",
"Manasi",
""
],
[
"Siu",
"Ho Chit",
""
],
[
"Paleja",
"Rohan",
""
],
[
"Peña",
"Jaime D.",
""
]
] |
2406.02338 | Michele Mastromattei | Michele Mastromattei, Fabio Massimo Zanzotto | Linguistic Fingerprint in Transformer Models: How Language Variation
Influences Parameter Selection in Irony Detection | null | Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP
(NLPerspectives) @ LREC-COLING 2024 | null | null | cs.CL cs.AI | http://creativecommons.org/publicdomain/zero/1.0/ | This paper explores the correlation between linguistic diversity, sentiment
analysis and transformer model architectures. We aim to investigate how
different English variations impact transformer-based models for irony
detection. To conduct our study, we used the EPIC corpus to extract five
diverse English variation-... | [
{
"created": "Tue, 4 Jun 2024 14:09:36 GMT",
"version": "v1"
}
] | 2024-06-05 | [
[
"Mastromattei",
"Michele",
""
],
[
"Zanzotto",
"Fabio Massimo",
""
]
] |
2406.02562 | Gwantae Kim | Gwantae Kim, Bokyeung Lee, Donghyeon Kim and Hanseok Ko | Gated Low-rank Adaptation for personalized Code-Switching Automatic
Speech Recognition on the low-spec devices | Table 2 is revised | ICASSP 2024 Workshop(HSCMA 2024) paper | null | null | eess.AS cs.AI cs.CL | http://creativecommons.org/licenses/by-nc-nd/4.0/ | In recent times, there has been a growing interest in utilizing personalized
large models on low-spec devices, such as mobile and CPU-only devices. However,
utilizing a personalized large model in the on-device is inefficient, and
sometimes limited due to computational cost. To tackle the problem, this paper
presents... | [
{
"created": "Wed, 24 Apr 2024 01:31:39 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Kim",
"Gwantae",
""
],
[
"Lee",
"Bokyeung",
""
],
[
"Kim",
"Donghyeon",
""
],
[
"Ko",
"Hanseok",
""
]
] |
2406.02579 | Louis Ledoux | Louis Ledoux and Marc Casas | An Open-Source Framework for Efficient Numerically-Tailored Computations | 6 pages, open-source | International Conference on Field Programmable Logic and
Applications 2023 | 10.1109/FPL60245.2023.00011 | null | cs.MS cs.AI cs.AR cs.LG cs.NA math.NA | http://creativecommons.org/licenses/by/4.0/ | We present a versatile open-source framework designed to facilitate
efficient, numerically-tailored Matrix-Matrix Multiplications (MMMs). The
framework offers two primary contributions: first, a fine-tuned, automated
pipeline for arithmetic datapath generation, enabling highly customizable
systolic MMM kernels; secon... | [
{
"created": "Wed, 29 May 2024 10:10:53 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Ledoux",
"Louis",
""
],
[
"Casas",
"Marc",
""
]
] |
2406.02591 | Ivan Dubrovsky | Ivan Dubrovsky, Andrei Dmitrenko, Aleksei Dmitrenko, Nikita Serov,
Vladimir Vinogradov | Unveiling the Potential of AI for Nanomaterial Morphology Prediction | null | Proceedings of the 41 st International Conference on Machine
Learning. PMLR 235, 2024, 11957--11978 | null | null | cs.LG cs.AI | http://creativecommons.org/licenses/by/4.0/ | Creation of nanomaterials with specific morphology remains a complex
experimental process, even though there is a growing demand for these materials
in various industry sectors. This study explores the potential of AI to predict
the morphology of nanoparticles within the data availability constraints. For
that, we fi... | [
{
"created": "Fri, 31 May 2024 19:16:07 GMT",
"version": "v1"
}
] | 2024-08-01 | [
[
"Dubrovsky",
"Ivan",
""
],
[
"Dmitrenko",
"Andrei",
""
],
[
"Dmitrenko",
"Aleksei",
""
],
[
"Serov",
"Nikita",
""
],
[
"Vinogradov",
"Vladimir",
""
]
] |
2406.02921 | Zhong Meng | Zhong Meng, Zelin Wu, Rohit Prabhavalkar, Cal Peyser, Weiran Wang,
Nanxin Chen, Tara N. Sainath, Bhuvana Ramabhadran | Text Injection for Neural Contextual Biasing | 5 pages, 1 figure | Interspeech 2024, Kos Island, Greece | null | null | cs.CL cs.AI cs.LG cs.NE eess.AS | http://creativecommons.org/licenses/by/4.0/ | Neural contextual biasing effectively improves automatic speech recognition
(ASR) for crucial phrases within a speaker's context, particularly those that
are infrequent in the training data. This work proposes contextual text
injection (CTI) to enhance contextual ASR. CTI leverages not only the paired
speech-text dat... | [
{
"created": "Wed, 5 Jun 2024 04:20:17 GMT",
"version": "v1"
},
{
"created": "Tue, 11 Jun 2024 04:11:56 GMT",
"version": "v2"
}
] | 2024-06-12 | [
[
"Meng",
"Zhong",
""
],
[
"Wu",
"Zelin",
""
],
[
"Prabhavalkar",
"Rohit",
""
],
[
"Peyser",
"Cal",
""
],
[
"Wang",
"Weiran",
""
],
[
"Chen",
"Nanxin",
""
],
[
"Sainath",
"Tara N.",
""
],
[
"Ramabhadr... |
2406.02996 | Wooseong Jeong | Wooseong Jeong, Kuk-Jin Yoon | Quantifying Task Priority for Multi-Task Optimization | null | CVPR 2024 | null | null | cs.LG cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The goal of multi-task learning is to learn diverse tasks within a single
unified network. As each task has its own unique objective function, conflicts
emerge during training, resulting in negative transfer among them. Earlier
research identified these conflicting gradients in shared parameters between
tasks and att... | [
{
"created": "Wed, 5 Jun 2024 06:52:29 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Jeong",
"Wooseong",
""
],
[
"Yoon",
"Kuk-Jin",
""
]
] |
2406.03030 | Ali Malik | Ali Malik, Stephen Mayhew, Chris Piech, Klinton Bicknell | From Tarzan to Tolkien: Controlling the Language Proficiency Level of
LLMs for Content Generation | null | In Findings of the Association for Computational Linguistics (ACL
2024) | null | null | cs.CL cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | We study the problem of controlling the difficulty level of text generated by
Large Language Models (LLMs) for contexts where end-users are not fully
proficient, such as language learners. Using a novel framework, we evaluate the
effectiveness of several key approaches for this task, including few-shot
prompting, sup... | [
{
"created": "Wed, 5 Jun 2024 07:57:17 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Malik",
"Ali",
""
],
[
"Mayhew",
"Stephen",
""
],
[
"Piech",
"Chris",
""
],
[
"Bicknell",
"Klinton",
""
]
] |
2406.03117 | Zhixun He | Zhixun He and Mukesh Singhal | VQUNet: Vector Quantization U-Net for Defending Adversarial Atacks by
Regularizing Unwanted Noise | 8 pages, 6 figures | 2024 7th International Conference on Machine Vision and
Applications (ICMVA) | 10.1145/3653946.3653957 | null | cs.CV | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Deep Neural Networks (DNN) have become a promising paradigm when developing
Artificial Intelligence (AI) and Machine Learning (ML) applications. However,
DNN applications are vulnerable to fake data that are crafted with adversarial
attack algorithms. Under adversarial attacks, the prediction accuracy of DNN
applicat... | [
{
"created": "Wed, 5 Jun 2024 10:10:03 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"He",
"Zhixun",
""
],
[
"Singhal",
"Mukesh",
""
]
] |
2406.03194 | Moises Diaz | Moises Diaz, Gioele Crispo, Antonio Parziale, Angelo Marcelli, Miguel
A. Ferrer | Writing Order Recovery in Complex and Long Static Handwriting | null | International Journal of Interactive Multimedia and Artificial
Intelligence, Volume 7, number 4, Pages 171-184, 2022 | 10.9781/ijimai.2021.04.003 | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The order in which the trajectory is executed is a powerful source of
information for recognizers. However, there is still no general approach for
recovering the trajectory of complex and long handwriting from static images.
Complex specimens can result in multiple pen-downs and in a high number of
trajectory crossin... | [
{
"created": "Wed, 5 Jun 2024 12:23:17 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Diaz",
"Moises",
""
],
[
"Crispo",
"Gioele",
""
],
[
"Parziale",
"Antonio",
""
],
[
"Marcelli",
"Angelo",
""
],
[
"Ferrer",
"Miguel A.",
""
]
] |
2406.03221 | Pierre Nugues | Pierre Nugues | Linking Named Entities in Diderot's \textit{Encyclop\'edie} to Wikidata | 6 pages, 3 figures | Proceedings of the 2024 Joint International Conference on
Computational Linguistics, Language Resources and Evaluation (LREC-COLING
2024), pp. 10610--10615 | null | null | cs.CL cs.IR | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Diderot's \textit{Encyclop\'edie} is a reference work from XVIIIth century in
Europe that aimed at collecting the knowledge of its era. \textit{Wikipedia}
has the same ambition with a much greater scope. However, the lack of digital
connection between the two encyclopedias may hinder their comparison and the
study of... | [
{
"created": "Wed, 5 Jun 2024 13:00:04 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Nugues",
"Pierre",
""
]
] |
2406.03245 | Aakash Gautam | Aakash Gautam | Reconfiguring Participatory Design to Resist AI Realism | 6 pages, 1 table | Participatory Design Conference 2024 | 10.1145/3661455.3669867 | null | cs.HC cs.AI cs.SI | http://creativecommons.org/licenses/by/4.0/ | The growing trend of artificial intelligence (AI) as a solution to social and
technical problems reinforces AI Realism -- the belief that AI is an inevitable
and natural order. In response, this paper argues that participatory design
(PD), with its focus on democratic values and processes, can play a role in
question... | [
{
"created": "Wed, 5 Jun 2024 13:21:46 GMT",
"version": "v1"
},
{
"created": "Sat, 8 Jun 2024 18:19:00 GMT",
"version": "v2"
}
] | 2024-06-11 | [
[
"Gautam",
"Aakash",
""
]
] |
2406.03359 | Cristhian David Forigua Diaz | Cristhian Forigua, Maria Escobar and Pablo Arbelaez | SuperFormer: Volumetric Transformer Architectures for MRI
Super-Resolution | null | 7th International Workshop, SASHIMI 2022, Held in Conjunction with
MICCAI 2022, Singapore, September 18, 2022, Proceedings | 10.1007/978-3-031-16980-9_13 | null | eess.IV cs.CV | http://creativecommons.org/licenses/by/4.0/ | This paper presents a novel framework for processing volumetric medical
information using Visual Transformers (ViTs). First, We extend the
state-of-the-art Swin Transformer model to the 3D medical domain. Second, we
propose a new approach for processing volumetric information and encoding
position in ViTs for 3D appl... | [
{
"created": "Wed, 5 Jun 2024 15:14:29 GMT",
"version": "v1"
}
] | 2024-06-06 | [
[
"Forigua",
"Cristhian",
""
],
[
"Escobar",
"Maria",
""
],
[
"Arbelaez",
"Pablo",
""
]
] |
2406.03388 | Joaquim Jorge | Alexandre Duarte, Francisco Fernandes, Jo\~ao M. Pereira, Catarina
Moreira, Jacinto C. Nascimento, Joaquim Jorge | SelfReDepth: Self-Supervised Real-Time Depth Restoration for
Consumer-Grade Sensors | 13pp, 5 figures, 1 table | Journal of Real-Time Image Processing 2024 | 10.1007/s11554-024-01491-z | null | cs.CV cs.AI cs.HC | http://creativecommons.org/licenses/by-sa/4.0/ | Depth maps produced by consumer-grade sensors suffer from inaccurate
measurements and missing data from either system or scene-specific sources.
Data-driven denoising algorithms can mitigate such problems. However, they
require vast amounts of ground truth depth data. Recent research has tackled
this limitation using... | [
{
"created": "Wed, 5 Jun 2024 15:38:02 GMT",
"version": "v1"
}
] | 2024-07-04 | [
[
"Duarte",
"Alexandre",
""
],
[
"Fernandes",
"Francisco",
""
],
[
"Pereira",
"João M.",
""
],
[
"Moreira",
"Catarina",
""
],
[
"Nascimento",
"Jacinto C.",
""
],
[
"Jorge",
"Joaquim",
""
]
] |
2406.03470 | Zekai Xu | Kang You, Zekai Xu, Chen Nie, Zhijie Deng, Qinghai Guo, Xiang Wang and
Zhezhi He | SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN | * These authors contributed equally to this work | International Conference on Machine Learning 2024 | null | null | cs.NE cs.AI | http://creativecommons.org/licenses/by/4.0/ | Spiking neural network (SNN) has attracted great attention due to its
characteristic of high efficiency and accuracy. Currently, the ANN-to-SNN
conversion methods can obtain ANN on-par accuracy SNN with ultra-low latency (8
time-steps) in CNN structure on computer vision (CV) tasks. However, as
Transformer-based netw... | [
{
"created": "Wed, 5 Jun 2024 17:24:07 GMT",
"version": "v1"
}
] | 2024-08-21 | [
[
"You",
"Kang",
""
],
[
"Xu",
"Zekai",
""
],
[
"Nie",
"Chen",
""
],
[
"Deng",
"Zhijie",
""
],
[
"Guo",
"Qinghai",
""
],
[
"Wang",
"Xiang",
""
],
[
"He",
"Zhezhi",
""
]
] |
2406.03512 | Nicolas Michael M\"uller | Nicolas M. M\"uller, Nicholas Evans, Hemlata Tak, Philip Sperl,
Konstantin B\"ottinger | Harder or Different? Understanding Generalization of Audio Deepfake
Detection | null | Interspeech 2024 | null | null | cs.SD cs.AI eess.AS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent research has highlighted a key issue in speech deepfake detection:
models trained on one set of deepfakes perform poorly on others. The question
arises: is this due to the continuously improving quality of Text-to-Speech
(TTS) models, i.e., are newer DeepFakes just 'harder' to detect? Or, is it
because deepfak... | [
{
"created": "Wed, 5 Jun 2024 10:33:15 GMT",
"version": "v1"
},
{
"created": "Fri, 7 Jun 2024 13:53:07 GMT",
"version": "v2"
},
{
"created": "Wed, 12 Jun 2024 16:54:01 GMT",
"version": "v3"
}
] | 2024-06-13 | [
[
"Müller",
"Nicolas M.",
""
],
[
"Evans",
"Nicholas",
""
],
[
"Tak",
"Hemlata",
""
],
[
"Sperl",
"Philip",
""
],
[
"Böttinger",
"Konstantin",
""
]
] |
2406.03556 | Utsab Saha | Utsab Saha, Sawradip Saha, Shaikh Anowarul Fattah, and Mohammad Saquib | Npix2Cpix: A GAN-Based Image-to-Image Translation Network With
Retrieval- Classification Integration for Watermark Retrieval From Historical
Document Images | null | IEEE Access 12 (2024) 95857-95870 | 10.1109/ACCESS.2024.3424662 | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | The identification and restoration of ancient watermarks have long been a
major topic in codicology and history. Classifying historical documents based
on watermarks is challenging due to their diversity, noisy samples, multiple
representation modes, and minor distinctions between classes and intra-class
variations. ... | [
{
"created": "Wed, 5 Jun 2024 18:10:49 GMT",
"version": "v1"
},
{
"created": "Wed, 24 Jul 2024 18:50:51 GMT",
"version": "v2"
},
{
"created": "Mon, 16 Sep 2024 05:14:14 GMT",
"version": "v3"
}
] | 2024-09-17 | [
[
"Saha",
"Utsab",
""
],
[
"Saha",
"Sawradip",
""
],
[
"Fattah",
"Shaikh Anowarul",
""
],
[
"Saquib",
"Mohammad",
""
]
] |
2406.03665 | Jihyeon Seong | Jihyeon Seong, Sekwang Oh, Jaesik Choi | Towards Dynamic Trend Filtering through Trend Point Detection with
Reinforcement Learning | 18 pages, 11 figures | IJCAI 2024 | null | null | cs.LG cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Trend filtering simplifies complex time series data by applying smoothness to
filter out noise while emphasizing proximity to the original data. However,
existing trend filtering methods fail to reflect abrupt changes in the trend
due to `approximateness,' resulting in constant smoothness. This
approximateness unifor... | [
{
"created": "Thu, 6 Jun 2024 00:50:22 GMT",
"version": "v1"
}
] | 2024-07-12 | [
[
"Seong",
"Jihyeon",
""
],
[
"Oh",
"Sekwang",
""
],
[
"Choi",
"Jaesik",
""
]
] |
2406.03859 | Moises Diaz | Miguel A. Ferrer, Josep A. Calduch-Giner, Moises D\'iaz, Javier Sosa,
Enrique Rosell-Moll, Judith Santana Abril, Graciela Santana Sosa, Tom\'as
Bautista Delgado, Cristina Carmona, Juan Antonio Martos-Sitcha, Enric
Cabruja, Juan Manuel Afonso, Aurelio Vega, Manuel Lozano, Juan Antonio
Montiel-Nelson, Jaume P\'er... | From operculum and body tail movements to different coupling of physical
activity and respiratory frequency in farmed gilthead sea bream and European
sea bass. Insights on aquaculture biosensing | null | Computers and Electronics in Agriculture, col.175,pp.105531,2020 | 10.1016/j.compag.2020.105531 | null | cs.CV q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The AEFishBIT tri-axial accelerometer was externally attached to the
operculum to assess the divergent activity and respiratory patterns of two
marine farmed fish, the gilthead sea bream (Sparus aurata) and European sea
bass (Dicentrarchus labrax). Analysis of raw data from exercised fish
highlighted the large amplit... | [
{
"created": "Thu, 6 Jun 2024 08:46:00 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Ferrer",
"Miguel A.",
""
],
[
"Calduch-Giner",
"Josep A.",
""
],
[
"Díaz",
"Moises",
""
],
[
"Sosa",
"Javier",
""
],
[
"Rosell-Moll",
"Enrique",
""
],
[
"Abril",
"Judith Santana",
""
],
[
"Sosa",
"Graciela San... |
2406.03881 | Matthias Sperber | Matthias Sperber, Ond\v{r}ej Bojar, Barry Haddow, D\'avid Javorsk\'y,
Xutai Ma, Matteo Negri, Jan Niehues, Peter Pol\'ak, Elizabeth Salesky,
Katsuhito Sudoh, Marco Turchi | Evaluating the IWSLT2023 Speech Translation Tasks: Human Annotations,
Automatic Metrics, and Segmentation | LREC-COLING2024 publication (with corrections for Table 3) | Proceedings of the 2024 Joint International Conference on
Computational Linguistics, Language Resources and Evaluation (LREC-COLING
2024) | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Human evaluation is a critical component in machine translation system
development and has received much attention in text translation research.
However, little prior work exists on the topic of human evaluation for speech
translation, which adds additional challenges such as noisy data and
segmentation mismatches. W... | [
{
"created": "Thu, 6 Jun 2024 09:18:42 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Sperber",
"Matthias",
""
],
[
"Bojar",
"Ondřej",
""
],
[
"Haddow",
"Barry",
""
],
[
"Javorský",
"Dávid",
""
],
[
"Ma",
"Xutai",
""
],
[
"Negri",
"Matteo",
""
],
[
"Niehues",
"Jan",
""
],
[
"Polák",... |
2406.03897 | Tzuf Paz-Argaman | Tzuf Paz-Argaman, Itai Mondshine, Asaf Achi Mordechai, and Reut
Tsarfaty | HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew | null | ACL 2024 Findings | null | null | cs.CL cs.AI | http://creativecommons.org/licenses/by/4.0/ | While large language models (LLMs) excel in various natural language tasks in
English, their performance in lower-resourced languages like Hebrew, especially
for generative tasks such as abstractive summarization, remains unclear. The
high morphological richness in Hebrew adds further challenges due to the
ambiguity ... | [
{
"created": "Thu, 6 Jun 2024 09:36:14 GMT",
"version": "v1"
},
{
"created": "Mon, 10 Jun 2024 05:45:25 GMT",
"version": "v2"
}
] | 2024-06-11 | [
[
"Paz-Argaman",
"Tzuf",
""
],
[
"Mondshine",
"Itai",
""
],
[
"Mordechai",
"Asaf Achi",
""
],
[
"Tsarfaty",
"Reut",
""
]
] |
2406.03901 | Adrian Galdran | Adrian Galdran | Polyp and Surgical Instrument Segmentation with Double Encoder-Decoder
Networks | null | NMI, Vol. 1 No. 1 (2021): MedAI: Transparency in Medical Image
Segmentation | 10.5617/nmi.9107 | null | eess.IV cs.CV cs.LG | http://creativecommons.org/licenses/by/4.0/ | This paper describes a solution for the MedAI competition, in which
participants were required to segment both polyps and surgical instruments from
endoscopic images. Our approach relies on a double encoder-decoder neural
network which we have previously applied for polyp segmentation, but with a
series of enhancemen... | [
{
"created": "Thu, 6 Jun 2024 09:37:46 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Galdran",
"Adrian",
""
]
] |
2406.03984 | Sofija Engelson | Sofija Engelson, Jan Ehrhardt, Timo Kepp, Joshua Niemeijer and Heinz
Handels | LNQ Challenge 2023: Learning Mediastinal Lymph Node Segmentation with a
Probabilistic Lymph Node Atlas | Accepted for publication at the Journal of Machine Learning for
Biomedical Imaging (MELBA) https://melba-journal.org/2024:009 | Machine.Learning.for.Biomedical.Imaging. 2 (2024) | 10.59275/j.melba.2024-009 | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | The evaluation of lymph node metastases plays a crucial role in achieving
precise cancer staging, influencing subsequent decisions regarding treatment
options. Lymph node detection poses challenges due to the presence of unclear
boundaries and the diverse range of sizes and morphological characteristics,
making it a ... | [
{
"created": "Thu, 6 Jun 2024 11:57:25 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Engelson",
"Sofija",
""
],
[
"Ehrhardt",
"Jan",
""
],
[
"Kepp",
"Timo",
""
],
[
"Niemeijer",
"Joshua",
""
],
[
"Handels",
"Heinz",
""
]
] |
2406.03986 | Ankan Mullick | Ankan Mullick, Sombit Bose, Rounak Saha, Ayan Kumar Bhowmick, Pawan
Goyal, Niloy Ganguly, Prasenjit Dey, Ravi Kokku | On The Persona-based Summarization of Domain-Specific Documents | null | ACL 2024 Findings (Association for Computational Linguistics) | null | null | cs.CL cs.IR | http://creativecommons.org/publicdomain/zero/1.0/ | In an ever-expanding world of domain-specific knowledge, the increasing
complexity of consuming, and storing information necessitates the generation of
summaries from large information repositories. However, every persona of a
domain has different requirements of information and hence their summarization.
For example... | [
{
"created": "Thu, 6 Jun 2024 12:00:41 GMT",
"version": "v1"
}
] | 2024-06-10 | [
[
"Mullick",
"Ankan",
""
],
[
"Bose",
"Sombit",
""
],
[
"Saha",
"Rounak",
""
],
[
"Bhowmick",
"Ayan Kumar",
""
],
[
"Goyal",
"Pawan",
""
],
[
"Ganguly",
"Niloy",
""
],
[
"Dey",
"Prasenjit",
""
],
[
"K... |
2406.04050 | Thomas Schmitt | Thomas H. Schmitt, Maximilian Bundscherer and Tobias Bocklet | Semmeldetector: Application of Machine Learning in Commercial Bakeries | null | 2023 International Conference on Machine Learning and Applications
(ICMLA), IEEE, 2023, pp. 878-883 | null | null | cs.CV | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The Semmeldetector, is a machine learning application that utilizes object
detection models to detect, classify and count baked goods in images. Our
application allows commercial bakers to track unsold baked goods, which allows
them to optimize production and increase resource efficiency. We compiled a
dataset compri... | [
{
"created": "Thu, 6 Jun 2024 13:17:24 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Schmitt",
"Thomas H.",
""
],
[
"Bundscherer",
"Maximilian",
""
],
[
"Bocklet",
"Tobias",
""
]
] |
2406.04101 | Yihang Chen | Yihang Chen, Qianyi Wu, Mehrtash Harandi, Jianfei Cai | How Far Can We Compress Instant-NGP-Based NeRF? | Project Page: https://yihangchen-ee.github.io/project_cnc/ Code:
https://github.com/yihangchen-ee/cnc/. We further propose a 3DGS compression
method HAC, which is based on CNC:
https://yihangchen-ee.github.io/project_hac/ | CVPR 2024 | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In recent years, Neural Radiance Field (NeRF) has demonstrated remarkable
capabilities in representing 3D scenes. To expedite the rendering process,
learnable explicit representations have been introduced for combination with
implicit NeRF representation, which however results in a large storage space
requirement. In... | [
{
"created": "Thu, 6 Jun 2024 14:16:03 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Chen",
"Yihang",
""
],
[
"Wu",
"Qianyi",
""
],
[
"Harandi",
"Mehrtash",
""
],
[
"Cai",
"Jianfei",
""
]
] |
2406.04109 | Adil Soubki | Adil Soubki and Owen Rambow | Intention and Face in Dialog | null | May 2024. In Proceedings of the 2024 Joint International
Conference on Computational Linguistics, Language Resources and Evaluation
(LREC-COLING 2024), pages 9143-9153, Torino, Italia. ELRA and ICCL | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The notion of face described by Brown and Levinson (1987) has been studied in
great detail, but a critical aspect of the framework, that which focuses on how
intentions mediate the planning of turns which impose upon face, has received
far less attention. We present an analysis of three computational systems
trained ... | [
{
"created": "Thu, 6 Jun 2024 14:26:35 GMT",
"version": "v1"
}
] | 2024-06-07 | [
[
"Soubki",
"Adil",
""
],
[
"Rambow",
"Owen",
""
]
] |
2406.04624 | Vipin Venugopal | Vipin V | Image Processing Based Forest Fire Detection | 9 pages | International Journal of Emerging Technology and Advanced
Engineering, 2(2), 87-95 (2012) | null | null | cs.CV cs.LG | http://creativecommons.org/licenses/by/4.0/ | A novel approach for forest fire detection using image processing technique
is proposed. A rule-based color model for fire pixel classification is used.
The proposed algorithm uses RGB and YCbCr color space. The advantage of using
YCbCr color space is that it can separate the luminance from the chrominance
more effec... | [
{
"created": "Fri, 7 Jun 2024 04:11:45 GMT",
"version": "v1"
}
] | 2024-06-10 | [
[
"V",
"Vipin",
""
]
] |
2406.04713 | Benjamin Miller | Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M Wood | FlowMM: Generating Materials with Riemannian Flow Matching | https://github.com/facebookresearch/flowmm | ICML 2024 | null | null | cs.LG cond-mat.mtrl-sci cs.AI physics.comp-ph stat.ML | http://creativecommons.org/licenses/by/4.0/ | Crystalline materials are a fundamental component in next-generation
technologies, yet modeling their distribution presents unique computational
challenges. Of the plausible arrangements of atoms in a periodic lattice only a
vanishingly small percentage are thermodynamically stable, which is a key
indicator of the ma... | [
{
"created": "Fri, 7 Jun 2024 07:46:23 GMT",
"version": "v1"
}
] | 2024-06-10 | [
[
"Miller",
"Benjamin Kurt",
""
],
[
"Chen",
"Ricky T. Q.",
""
],
[
"Sriram",
"Anuroop",
""
],
[
"Wood",
"Brandon M",
""
]
] |
2406.05443 | Asmaa Benchama | Asmaa Benchama, Khalid Zebbara | Novel Approach to Intrusion Detection: Introducing GAN-MSCNN-BILSTM with
LIME Predictions | null | Data and Metadata, 2023 Dec. 28 | 10.56294/dm2023202 | null | cs.CR cs.AI cs.NI | http://creativecommons.org/licenses/by/4.0/ | This paper introduces an innovative intrusion detection system that harnesses
Generative Adversarial Networks (GANs), Multi-Scale Convolutional Neural
Networks (MSCNNs), and Bidirectional Long Short-Term Memory (BiLSTM) networks,
supplemented by Local Interpretable Model-Agnostic Explanations (LIME) for
interpretabil... | [
{
"created": "Sat, 8 Jun 2024 11:26:44 GMT",
"version": "v1"
}
] | 2024-06-11 | [
[
"Benchama",
"Asmaa",
""
],
[
"Zebbara",
"Khalid",
""
]
] |
2406.05506 | Lior Limonad | Fabiana Fournier, Lior Limonad, Inna Skarbovsky | Towards a Benchmark for Causal Business Process Reasoning with LLMs | 12 pages, 1 figure | NLP4BPM workshop at BPM 2024 | null | null | cs.AI | http://creativecommons.org/licenses/by/4.0/ | Large Language Models (LLMs) are increasingly used for boosting
organizational efficiency and automating tasks. While not originally designed
for complex cognitive processes, recent efforts have further extended to employ
LLMs in activities such as reasoning, planning, and decision-making. In
business processes, such... | [
{
"created": "Sat, 8 Jun 2024 16:10:53 GMT",
"version": "v1"
},
{
"created": "Tue, 16 Jul 2024 15:48:32 GMT",
"version": "v2"
}
] | 2024-08-13 | [
[
"Fournier",
"Fabiana",
""
],
[
"Limonad",
"Lior",
""
],
[
"Skarbovsky",
"Inna",
""
]
] |
2406.05535 | Junqi Gao | Junqi Gao, Biqing Qi, Yao Li, Zhichang Guo, Dong Li, Yuming Xing,
Dazhi Zhang | Perturbation Towards Easy Samples Improves Targeted Adversarial
Transferability | null | Advances in Neural Information Processing Systems 36, 2023 | null | null | cs.LG cs.AI cs.CR | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The transferability of adversarial perturbations provides an effective
shortcut for black-box attacks. Targeted perturbations have greater
practicality but are more difficult to transfer between models. In this paper,
we experimentally and theoretically demonstrated that neural networks trained
on the same dataset ha... | [
{
"created": "Sat, 8 Jun 2024 17:33:23 GMT",
"version": "v1"
}
] | 2024-06-11 | [
[
"Gao",
"Junqi",
""
],
[
"Qi",
"Biqing",
""
],
[
"Li",
"Yao",
""
],
[
"Guo",
"Zhichang",
""
],
[
"Li",
"Dong",
""
],
[
"Xing",
"Yuming",
""
],
[
"Zhang",
"Dazhi",
""
]
] |
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