Good Papers

Showing papers from , Chinese Academy of Sciences Show all papers

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Institute of Computing Technolog, Chinese Academy of SciencesZhongguancun LaboratoryAI oversight & deception

OASIS: Online Adaptive Steering for In-Training Safety of LLMs

Yifan Sun, Qiang Sheng, Ya Wu, Zhengjia Wang and 4 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Tsinghua, Chinese Academy of SciencesMechanistic interpretability

From Groups to Rings: Causal Evidence for Algebraic Decomposition in Grokked Transformers

Shurui Zheng, Fanhong Li, Zhixing Huang, Zixi Li and 1 more

Sydney Poster Session 6, Thu, Dec 10, 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 2026Institute of Computing Technolog, Chinese Academy of SciencesU the Chinese Academy of ScienceMulti-agent RL

DDACOM: Dual-Decoupled Adaptive Communication for Multi-Agent Reinforcement Learning under Dynamic Networks

Yiqun Wu, QI WANG, Mengxian Li, Yongjun Xu

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
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026, Chinese Academy of SciencesInstitute of Computing TechnologU Chinese Academy of ScienceInsititute of Computing TechnoloInstitute of Computing, Chinese Materials & chemistry

Flux: Online, Fine-Grained Data Scheduling for Training Machine Learning Interatomic Potentials

Yuanchang Zhou, Chen Wang, Hongtao Xu, Mingzhen Li and 2 more

Sydney Poster Session 1, Tue, Dec 8, 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 2026Institute of Computing Technolog, Chinese Academy of SciencesU Chinese Academy of ScienceInsititute of Computing TechnoloPhysics-informed ML & PDEs

Verigrad: Verification-Driven Multi-Agent GPU Kernel Generation for High-Order MLIP Derivatives

yao liu, Yuanchang Zhou, Hongtao Xu, Mingzhen Li

Sydney Poster Session 5, Thu, Dec 10, 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U the Chinese Academy of ScienceInstitute of Computing TechnologLenovoTsinghua University, TsinghuaLenovo ResearchObject detection

Generative Object Detection with Co-Training

Yang Liu, Yao Zhang, Feng Hou, Yangzhou Du and 5 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · 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 2026HunanHunan University of Science and , Chinese Academy of SciencesCNIC CASHong Kong PolytechnicGraph transformers

DTA-GT: Direction- and Topology-Aware Graph Transformer for Neural Network Representation Learning

Yuxiang Zeng, Kun Xie, Yang Wang, Jigang Wen and 4 more

Sydney Poster Session 6, Thu, Dec 10, 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
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026, Chinese Academy of SciencesTencent AI LabChinese Academy of SciencesAlibaba GroupInstitute of Computing TechnologUnified multimodal models

AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling

AnyMo introduces OmniHuMo dataset with 5,000 hours of multimodal motion data and proposes a masked modeling framework for scalable any-modality conditional motion synthesis with flexible spatial and stylistic control.

Yiheng Li, Zhuo Li, RuiBing Hou, Yingjie Chen and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 2 on Hugging Face

– ReadersNo votes yet
9/20 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: 9 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 1/5
76%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026State Key Laboratory of ProcessoNanjingU Science and Technology of ChinInstitute of Computing TechnologMegvii Technology Inc.Vision-language-action models

Realtime-VLA FLASH: Speculative Inference Framework for Diffusion-based VLAs

Realtime-VLA FLASH uses a draft model and parallel verification to replace most full diffusion-based VLA inference rounds with faster speculative ones, cutting average latency 3.04x to 19.1 ms.

Jiahui Niu, Kefan Gu, Yucheng Zhao, shengwen Liang and 4 more

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

– 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
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 of Computing TechnologBaidu, Chinese Academy of SciencesXiaohongshuAlibabaLLM agents & planning

Knowledge-Graph Paths as Intermediate Supervision for Self-Evolving Search Agents

Knowledge-graph paths provide intermediate supervision for self-evolving search agents, improving question validity via relational context and solver rewards via waypoint coverage, boosting multi-hop QA across benchmarks.

Huyu Wu, Jun Liu, Xiaochi Wei, Yan Gao and 2 more

Sydney Poster Session 1, Tue, Dec 8, 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 4/5
medium 9/10
strict 1/5