Good Papers

Showing papers from Institute for AI Industry Research, Tsinghua University Show all papers

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026TsinghuaShanghai AI LaboratoryInstitute for AI Industry ResearInstitute for AI Industry ResearCode generation

Learning to Commit: Next-Commit Prediction via Online Supervised Contrastive Reflection

Mo Li, Qitai Tan, Kai Chen, Ting Cao and 1 more

Sydney Poster Session 5, Thu, Dec 10, 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 2026Beijing JiaotongU Electronic Science and TechnolInstitute for AI Industry ResearHorizon RoboticsCarizonDeep RL

Higher-Order Action Supervision Makes A Strong Policy Class

Peng Cheng, Yunxian Hou, Zhi Zhou, Qian Zhang and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 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 2026TsinghuaInstitute for AI Industry ResearInstitute of AI Industry ResearcU the Chinese Academy of ScienceDell TechnologyLLM evaluation & benchmarks

CSBench: A Comprehensive Benchmark for Evaluating Project-Level System Construction in Computer Science

Hongli Yu, Huan-ang Gao, Botian Wang, Hanlin Wu and 11 more

Sydney Poster Session 3, Wed, Dec 9, 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 Hong Kong University of ScieTsinghuaInstitute for AI Industry ResearRepresentation & contrastive learning

LogicSR: A Unified Benchmark for Logical Discovery from Data

Zimeng Zhang, Xin Zheng, Feifei Zhang, Yunxin Liu and 1 more

Sydney Poster Session 3, Wed, Dec 9, 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
72%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026SichuanU the Chinese Academy of SciencePeking, Chinese Academy of SciencesInstitute for AI Industry ResearMaterials & chemistry

AtomWorld-Mem: Memory-Restored World States for Long-Horizon Atomistic Evolution

AtomWorld-Mem restores latent hidden dynamical states from atomistic snapshots via multi-scale memory to improve long-horizon kinetic Monte Carlo evolution and transfer across unseen alloys.

Tian Luo, Ruge Zhang, Haozhi Han, Yifeng Chen and 4 more

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

– ReadersNo votes yet
8/20 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: 8 of 20 reviewers recommend it
lenient 3/5
medium 5/10
strict 0/5
86%Must read
?Must readVote to see the score
NeurIPS 2026Institute for AI Industry ResearTsinghuaInstitute for AI Industry ResearTsinghua University, TsinghuaProteins

Structure-aware Reinforcement Learning for Protein Directed Evolution

StructEvo uses structure-aware reinforcement learning with delta-structure fusion and hierarchical actions to outperform state-of-the-art protein directed evolution methods by up to 16.3%.

Zikun Nie, Suyuan Zhao, Yizhen Luo, Siqi Fan and 1 more

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

– ReadersNo votes yet
14/20 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: 14 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 0/5