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Collections including paper arxiv:2503.02130

Depth Anything V2

Paper • 2406.09414 • Published Jun 13, 2024 • 103
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels

Paper • 2406.09415 • Published Jun 13, 2024 • 51
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion

Paper • 2406.04338 • Published Jun 6, 2024 • 39
SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1, 2024 • 122

You Do Not Fully Utilize Transformer's Representation Capacity

Paper • 2502.09245 • Published Feb 13, 2025 • 37
LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers

Paper • 2502.15007 • Published Feb 20, 2025 • 175
Transformers without Normalization

Paper • 2503.10622 • Published Mar 13, 2025 • 172
Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32

RuCCoD: Towards Automated ICD Coding in Russian

Paper • 2502.21263 • Published Feb 28, 2025 • 133
Unified Reward Model for Multimodal Understanding and Generation

Paper • 2503.05236 • Published Mar 7, 2025 • 124
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching

Paper • 2503.05179 • Published Mar 7, 2025 • 46
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Paper • 2503.05592 • Published Mar 7, 2025 • 27

I don't know how to use it, but looks good.

Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32

about Transformer

What Matters in Transformers? Not All Attention is Needed

Paper • 2406.15786 • Published Jun 22, 2024 • 33
Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss

Paper • 2410.17243 • Published Oct 22, 2024 • 92
Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32
Transformers without Normalization

Paper • 2503.10622 • Published Mar 13, 2025 • 172

NN Arch Components

A Unified View of Attention and Residual Sinks: Outlier-Driven Rescaling is Essential for Transformer Training

Paper • 2601.22966 • Published Jan 30
STEM: Scaling Transformers with Embedding Modules

Paper • 2601.10639 • Published Jan 15 • 2
Deep Delta Learning

Paper • 2601.00417 • Published Jan 1 • 34
mHC: Manifold-Constrained Hyper-Connections

Paper • 2512.24880 • Published Dec 31, 2025 • 322

Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models

Paper • 2502.15086 • Published Feb 20, 2025 • 16
Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32

Foundational Deep Learning - Architecture

Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32
L^2M: Mutual Information Scaling Law for Long-Context Language Modeling

Paper • 2503.04725 • Published Mar 6, 2025 • 21
Transformers without Normalization

Paper • 2503.10622 • Published Mar 13, 2025 • 172
I-Con: A Unifying Framework for Representation Learning

Paper • 2504.16929 • Published Apr 23, 2025 • 30

LM2: Large Memory Models

Paper • 2502.06049 • Published Feb 9, 2025 • 31
Titans: Learning to Memorize at Test Time

Paper • 2501.00663 • Published Dec 31, 2024 • 31
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28, 2025 • 125
You Do Not Fully Utilize Transformer's Representation Capacity

Paper • 2502.09245 • Published Feb 13, 2025 • 37

LLM Pruning and Distillation in Practice: The Minitron Approach

Paper • 2408.11796 • Published Aug 21, 2024 • 60
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Paper • 2408.09174 • Published Aug 17, 2024 • 53
To Code, or Not To Code? Exploring Impact of Code in Pre-training

Paper • 2408.10914 • Published Aug 20, 2024 • 45
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications

Paper • 2408.11878 • Published Aug 20, 2024 • 64

Depth Anything V2

Paper • 2406.09414 • Published Jun 13, 2024 • 103
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels

Paper • 2406.09415 • Published Jun 13, 2024 • 51
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion

Paper • 2406.04338 • Published Jun 6, 2024 • 39
SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1, 2024 • 122

NN Arch Components

A Unified View of Attention and Residual Sinks: Outlier-Driven Rescaling is Essential for Transformer Training

Paper • 2601.22966 • Published Jan 30
STEM: Scaling Transformers with Embedding Modules

Paper • 2601.10639 • Published Jan 15 • 2
Deep Delta Learning

Paper • 2601.00417 • Published Jan 1 • 34
mHC: Manifold-Constrained Hyper-Connections

Paper • 2512.24880 • Published Dec 31, 2025 • 322

You Do Not Fully Utilize Transformer's Representation Capacity

Paper • 2502.09245 • Published Feb 13, 2025 • 37
LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers

Paper • 2502.15007 • Published Feb 20, 2025 • 175
Transformers without Normalization

Paper • 2503.10622 • Published Mar 13, 2025 • 172
Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32

Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models

Paper • 2502.15086 • Published Feb 20, 2025 • 16
Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32

RuCCoD: Towards Automated ICD Coding in Russian

Paper • 2502.21263 • Published Feb 28, 2025 • 133
Unified Reward Model for Multimodal Understanding and Generation

Paper • 2503.05236 • Published Mar 7, 2025 • 124
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching

Paper • 2503.05179 • Published Mar 7, 2025 • 46
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Paper • 2503.05592 • Published Mar 7, 2025 • 27

Foundational Deep Learning - Architecture

Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32
L^2M: Mutual Information Scaling Law for Long-Context Language Modeling

Paper • 2503.04725 • Published Mar 6, 2025 • 21
Transformers without Normalization

Paper • 2503.10622 • Published Mar 13, 2025 • 172
I-Con: A Unifying Framework for Representation Learning

Paper • 2504.16929 • Published Apr 23, 2025 • 30

I don't know how to use it, but looks good.

Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32

LM2: Large Memory Models

Paper • 2502.06049 • Published Feb 9, 2025 • 31
Titans: Learning to Memorize at Test Time

Paper • 2501.00663 • Published Dec 31, 2024 • 31
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28, 2025 • 125
You Do Not Fully Utilize Transformer's Representation Capacity

Paper • 2502.09245 • Published Feb 13, 2025 • 37

about Transformer

What Matters in Transformers? Not All Attention is Needed

Paper • 2406.15786 • Published Jun 22, 2024 • 33
Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss

Paper • 2410.17243 • Published Oct 22, 2024 • 92
Forgetting Transformer: Softmax Attention with a Forget Gate

Paper • 2503.02130 • Published Mar 3, 2025 • 32
Transformers without Normalization

Paper • 2503.10622 • Published Mar 13, 2025 • 172

LLM Pruning and Distillation in Practice: The Minitron Approach

Paper • 2408.11796 • Published Aug 21, 2024 • 60
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Paper • 2408.09174 • Published Aug 17, 2024 • 53
To Code, or Not To Code? Exploring Impact of Code in Pre-training

Paper • 2408.10914 • Published Aug 20, 2024 • 45
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications

Paper • 2408.11878 • Published Aug 20, 2024 • 64

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