Datasets:

JerMa88
/

ICLR_Peer_Reviews

relative_rank int64 0 16.8k	win_prob float64 0.01 0.99	title stringlengths 8 158	abstract stringlengths 227 2.78k	full_text stringlengths 76 184k	review stringlengths 62 28.2k	source stringclasses 4 values	review_src stringclasses 1 value	criteria_count dict	dimension_scores dict	overall_score float64 0 6	thinking_trace stringlengths 5 6.3k	prompt stringlengths 636 184k	prompt_length int64 120 82.1k	conversations listlengths 2 2	year int64 2.02k 2.02k
0	0.992632	Representational Disentanglement for Multi-Domain Image Completion	Multi-domain data are widely leveraged in vision applications to take advantage of complementary information from each modality, e.g., brain tumor segmentation from multi-parametric magnetic resonance imaging (MRI). However, due to different imaging protocol and data loss or corruption, the availability of images in al...	Title: REPRESENTATIONAL DISENTANGLEMENT FOR MULTI-DOMAIN IMAGE COMPLETION Abstract: Multi-domain data are widely leveraged in vision applications to take advantage of complementary information from each modality, e.g., brain tumor segmentation from multi-parametric magnetic resonance imaging (MRI). However, due to dif...	[Summary] This paper proposes an image translation method that generates images of missing domains from images in multiple available domains. i.e., ReMIC. For achieving this, the authors employ using separated latent codes for content and style from shared representation. They compare the proposed model with StarGAN, M...	iclr2020	OpenReview	{ "criticism": 3, "example": 2, "importance_and_relevance": 1, "materials_and_methods": 14, "praise": 3, "presentation_and_reporting": 6, "results_and_discussion": 2, "suggestion_and_solution": 5, "total": 23 }	{ "criticism": 0.13043478260869565, "example": 0.08695652173913043, "importance_and_relevance": 0.043478260869565216, "materials_and_methods": 0.6086956521739131, "praise": 0.13043478260869565, "presentation_and_reporting": 0.2608695652173913, "results_and_discussion": 0.08695652173913043, "suggestion_a...	1.565217	Let me review this paper on "Representational Disentanglement for Multi-Domain Image Completion" to provide a comprehensive peer review. First, I'll summarize the paper: - The paper proposes a generative adversarial network (GAN) architecture called ReMIC that addresses the problem of multi-domain image completion (ha...	You are a member of the scientific community tasked with peer review. Review the following paper content. ### Paper Content Title: REPRESENTATIONAL DISENTANGLEMENT FOR MULTI-DOMAIN IMAGE COMPLETION Abstract: Multi-domain data are widely leveraged in vision applications to take advantage of complementary information ...	12,166	[ { "content": "You are a member of the scientific community tasked with peer review. Review the following paper content.\n\n### Paper Content\n\nTitle: REPRESENTATIONAL DISENTANGLEMENT FOR MULTI-DOMAIN IMAGE COMPLETION\n\nAbstract: Multi-domain data are widely leveraged in vision applications to take advantage o...	2,020
19	0.970107	Representational Disentanglement for Multi-Domain Image Completion	"Multi-domain data are widely leveraged in vision applications to take advantage of complementary in(...TRUNCATED)	"Title: REPRESENTATIONAL DISENTANGLEMENT FOR MULTI-DOMAIN IMAGE COMPLETION\n\nAbstract: Multi-domain(...TRUNCATED)	"In this work, the authors proposed a deep learning-based method for synthesizing the missing modali(...TRUNCATED)	iclr2020	OpenReview	{"criticism":10,"example":5,"importance_and_relevance":0,"materials_and_methods":38,"praise":2,"pres(...TRUNCATED)	{"criticism":0.11494252873563218,"example":0.05747126436781609,"importance_and_relevance":0.0,"mater(...TRUNCATED)	0.954023	"Let me review this paper on \"Representational Disentanglement for Multi-Domain Image Completion\" (...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	12,166	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,020
3,886	0.759604	Representational Disentanglement for Multi-Domain Image Completion	"Multi-domain data are widely leveraged in vision applications to take advantage of complementary in(...TRUNCATED)	"Title: REPRESENTATIONAL DISENTANGLEMENT FOR MULTI-DOMAIN IMAGE COMPLETION\n\nAbstract: Multi-domain(...TRUNCATED)	"Overall, I think the authors tackle a meaningful task of translating images when not all modes are (...TRUNCATED)	iclr2020	OpenReview	{"criticism":14,"example":0,"importance_and_relevance":2,"materials_and_methods":15,"praise":2,"pres(...TRUNCATED)	{"criticism":0.3783783783783784,"example":0.0,"importance_and_relevance":0.05405405405405406,"materi(...TRUNCATED)	1.756757	"Let me review this paper on \"Representational Disentanglement for Multi-Domain Image Completion\" (...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	12,166	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,020
1	0.987938	"Baseline-corrected space-by-time non-negative matrix factorization for decoding single trial popula(...TRUNCATED)	"Activity of populations of sensory neurons carries stimulus information in both the temporal and th(...TRUNCATED)	"Title: BASELINE-CORRECTED SPACE-BY-TIME NON-NEGATIVE MATRIX FACTORIZATION FOR DECODING SINGLE TRIAL(...TRUNCATED)	" In this paper, the authors present an adaptation of space-by-time non-negative matrix factorizatio(...TRUNCATED)	iclr2018	OpenReview	{"criticism":2,"example":0,"importance_and_relevance":0,"materials_and_methods":6,"praise":0,"presen(...TRUNCATED)	{"criticism":0.2222222222222222,"example":0.0,"importance_and_relevance":0.0,"materials_and_methods"(...TRUNCATED)	1.222222	"I'll review this scientific paper on \"BASELINE-CORRECTED SPACE-BY-TIME NON-NEGATIVE MATRIX FACTORI(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	6,908	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,018
11	0.976972	"Baseline-corrected space-by-time non-negative matrix factorization for decoding single trial popula(...TRUNCATED)	"Activity of populations of sensory neurons carries stimulus information in both the temporal and th(...TRUNCATED)	"Title: BASELINE-CORRECTED SPACE-BY-TIME NON-NEGATIVE MATRIX FACTORIZATION FOR DECODING SINGLE TRIAL(...TRUNCATED)	" In this contribution, the authors propose an improvement of a tensor decomposition method for deco(...TRUNCATED)	iclr2018	OpenReview	{"criticism":0,"example":1,"importance_and_relevance":1,"materials_and_methods":6,"praise":1,"presen(...TRUNCATED)	{"criticism":0.0,"example":0.14285714285714285,"importance_and_relevance":0.14285714285714285,"mater(...TRUNCATED)	2.142857	"I'll review this scientific paper on \"BASELINE-CORRECTED SPACE-BY-TIME NON-NEGATIVE MATRIX FACTORI(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	6,908	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,018
64	0.956668	"Baseline-corrected space-by-time non-negative matrix factorization for decoding single trial popula(...TRUNCATED)	"Activity of populations of sensory neurons carries stimulus information in both the temporal and th(...TRUNCATED)	"Title: BASELINE-CORRECTED SPACE-BY-TIME NON-NEGATIVE MATRIX FACTORIZATION FOR DECODING SINGLE TRIAL(...TRUNCATED)	" This study proposes the use of non-negative matrix factorization accounting for baseline by subtra(...TRUNCATED)	iclr2018	OpenReview	{"criticism":2,"example":0,"importance_and_relevance":2,"materials_and_methods":19,"praise":4,"prese(...TRUNCATED)	{"criticism":0.07692307692307693,"example":0.0,"importance_and_relevance":0.07692307692307693,"mater(...TRUNCATED)	1.846154	"I'll review this scientific paper on \"BASELINE-CORRECTED SPACE-BY-TIME NON-NEGATIVE MATRIX FACTORI(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	6,908	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,018
2	0.984691	Learning from Partially-Observed Multimodal Data with Variational Autoencoders	"Learning from only partially-observed data for imputation has been an active research area. Despite(...TRUNCATED)	"Title: LEARNING FROM PARTIALLY-OBSERVED MULTI-MODAL DATA WITH VARIATIONAL AUTOENCODERS\n\nAbstract:(...TRUNCATED)	"Summary: This paper proposes to impute multimodal data when certain modalities are present. The aut(...TRUNCATED)	iclr2020	OpenReview	{"criticism":4,"example":0,"importance_and_relevance":1,"materials_and_methods":14,"praise":3,"prese(...TRUNCATED)	{"criticism":0.21052631578947367,"example":0.0,"importance_and_relevance":0.05263157894736842,"mater(...TRUNCATED)	1.473684	"I need to provide a thorough peer review of this paper on Variational Selective Autoencoders (VSAE)(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	13,603	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,020
195	0.936464	Learning from Partially-Observed Multimodal Data with Variational Autoencoders	"Learning from only partially-observed data for imputation has been an active research area. Despite(...TRUNCATED)	"Title: LEARNING FROM PARTIALLY-OBSERVED MULTI-MODAL DATA WITH VARIATIONAL AUTOENCODERS\n\nAbstract:(...TRUNCATED)	"The paper proposed variational selective autoencoders (VSAE) to learn from partially-observed multi(...TRUNCATED)	iclr2020	OpenReview	{"criticism":14,"example":4,"importance_and_relevance":2,"materials_and_methods":25,"praise":6,"pres(...TRUNCATED)	{"criticism":0.2153846153846154,"example":0.06153846153846154,"importance_and_relevance":0.030769230(...TRUNCATED)	1.369231	"I need to provide a thorough peer review of this paper on Variational Selective Autoencoders (VSAE)(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	13,603	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,020
632	0.899001	Learning from Partially-Observed Multimodal Data with Variational Autoencoders	"Learning from only partially-observed data for imputation has been an active research area. Despite(...TRUNCATED)	"Title: LEARNING FROM PARTIALLY-OBSERVED MULTI-MODAL DATA WITH VARIATIONAL AUTOENCODERS\n\nAbstract:(...TRUNCATED)	"The paper proposes a novel training method for variational autoencoders that allows using partially(...TRUNCATED)	iclr2020	OpenReview	{"criticism":12,"example":4,"importance_and_relevance":2,"materials_and_methods":29,"praise":1,"pres(...TRUNCATED)	{"criticism":0.26666666666666666,"example":0.08888888888888889,"importance_and_relevance":0.04444444(...TRUNCATED)	1.733333	"I need to provide a thorough peer review of this paper on Variational Selective Autoencoders (VSAE)(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	13,603	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,020
1,713	0.841589	Learning from Partially-Observed Multimodal Data with Variational Autoencoders	"Learning from only partially-observed data for imputation has been an active research area. Despite(...TRUNCATED)	"Title: LEARNING FROM PARTIALLY-OBSERVED MULTI-MODAL DATA WITH VARIATIONAL AUTOENCODERS\n\nAbstract:(...TRUNCATED)	"This paper proposes variational selective autoencoders (VSAE) to learn the joint distribution model(...TRUNCATED)	iclr2020	OpenReview	{"criticism":2,"example":0,"importance_and_relevance":1,"materials_and_methods":11,"praise":3,"prese(...TRUNCATED)	{"criticism":0.13333333333333333,"example":0.0,"importance_and_relevance":0.06666666666666667,"mater(...TRUNCATED)	1.533333	"I need to provide a thorough peer review of this paper on Variational Selective Autoencoders (VSAE)(...TRUNCATED)	"You are a member of the scientific community tasked with peer review. Review the following paper co(...TRUNCATED)	13,603	[{"content":"You are a member of the scientific community tasked with peer review. Review the follow(...TRUNCATED)	2,020

End of preview. Expand in Data Studio

ICLR Peer Reviews Dataset

This dataset contains peer reviews from ICLR (International Conference on Learning Representations), processed and standardized.

Dataset Structure

title: Title of the paper
abstract: Abstract of the paper
full_text: Full text of the paper (if available)
review: The peer review text
source: Source conference/year (e.g., iclr2020)
review_src: Original source identifier
year: Year of the conference (extracted from source)
overall_score: Computed overall quality score
dimension_scores: Scores for specific dimensions (criticism, praise, etc.)
criteria_count: Count of sentences matching specific criteria
conversations: Chat-style format of the review

Usage

from datasets import load_dataset
ds = load_dataset("JerMa88/ICLR_Peer_Reviews")

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