Good Papers

Showing papers from RIKEN / University of Tokyo Show all papers

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U TokyoRIKENThe University of Tokyo / RIKEN The University of Tokyo; RIKEN ARIKEN/University of TokyoSemi- & weakly supervised learning

Rethinking Learning from Label Proportions via Moment Matching

Tianhao Ma, Wei Wang, Yivan Zhang, Dong-Dong Wu and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026The University of TokyoRIKEN / University of TokyoDiffusion models

Asymptotically Exact Negative Guidance of Diffusion Models via Positive-Unlabeled Learning

Hirohane Takagi, Masashi Sugiyama

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Tohoku University, Institute of RIKEN AIPMicrosoft ResearchRIKEN/University of TokyoRIKENFairness & bias

Practical Estimation of the Bayes Optimal Fairness-Accuracy Tradeoff with Soft Labels

mohit sharma, Okan Koc, Amit Jayant Deshpande, Takashi Ishida and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026The University of Tokyo; RIKEN AMBZUAIRIKENMohamed bin Zayed University of RIKEN / University of TokyoDiffusion models

DELTA: Robustly Training Label-Conditional Diffusion Models with Weak Annotations

Dong-Dong Wu, Jiacheng Cui, Wei Wang, Zhiqiang Shen and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
76%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026JilinRIKEN-AIPThe University of WarwickRIKENRIKEN / University of TokyoInstruction tuning

Estimating and Orthogonalizing Unknown Pre-training Gradients for Continual Fine-tuning of Large Language Models

EoupCT estimates unknown pre-training gradients via learnable pseudo-data prompts and orthogonalizes updates to preserve general knowledge during continual LLM fine-tuning.

Bing Wang, Changchun Li, Xin-Qiang Cai, Lin Y Wu and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 0/5