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Showing papers from Institute of Software, Chinese Academy of Sciences Show all papers

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NeurIPS 2026U Chinese Academy of SciencesXiaohongshu IncU the Chinese Academy of ScienceSCIRInstitute of Software, Chinese AImitation learning

Your Teacher Can’t Help You Here: Combating Supervision Fidelity Decay in On-Policy Distillation

Yanjiang Liu, Jie Lou, Xinyan Guan, Yuqiu Ji and 6 more

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

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NeurIPS 2026Institute of Software, Chinese AU the Chinese Academy of ScienceBeijing University of AeronauticInstitute of Software, CASAlibaba GroupAgent benchmarks & environments

AutoDataBench: How Far Are LLM Agents from Autonomously Engineering Post-Training Data Pipelines?

Qiaoyu Tang, Hao Xiang, Le Yu, Yaojie Lu and 9 more

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

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57%Worth a look
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NeurIPS 2026U the Chinese Academy of ScienceInstitute of Software, Chinese AU Chinese Academy of SciencesChinese Academy of Sciences, InsOffline RL

OGPO: Offline Goal-conditioned Policy Optimization for Recoverable Vision-Language-Action Models

Xule Gao, Xi Wang, Zehua Zang, Rui Wang and 2 more

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

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lenient 1/5
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67%Highly rated
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NeurIPS 2026Institute of Software, Chinese AInstitute of Software, Chinese AU the Chinese Academy of SciencePekingTsinghuaEfficient inference & serving

LLMs Optimizing LLMs: Automated MegaKernel Generation for Inference Acceleration

Weiqiang Xiong, Shaohui Peng, Wenyi Li, Hao Lu and 7 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
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NeurIPS 2026Institute of Software, Chinese ANagoyaLearning theory

Quantum Composite Hypothesis Testing with Small Error

Chenghua Liu, Qisheng Wang

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

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NeurIPS 2026Institute of Software, Chinese ALLM evaluation & benchmarks

DIS-Bench: Evaluating LLMs on System Testing via Directed Input Synthesis

Siwei Wei, Yuqi Guo, Yan Cai

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

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lenient 1/5
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NeurIPS 2026ZhejiangByteDance Inc.Institute of Software, Chinese ARL for LLMs

GDMD: Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning

Linwei Dong, Ruoyu Guo, Ge Bai, Quan Zheng and 2 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U the Chinese Academy of ScienceInstitute of Software, Chinese ABeijing University of AeronauticInstitute of Software, CASU Chinese Academy of SciencesRL for LLMs

Verifiable Environments Are LEGO Bricks: Recursive Composition for Reasoning Generalization

RACES recursively composes verifiable environments as LEGO bricks to scale RL reasoning training, boosting model performance on unseen benchmarks with far fewer base environments.

Hao Xiang, Qiaoyu Tang, Le Yu, Yaojie Lu and 7 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 8 on Hugging Face

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 0/5
78%Highly rated
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NeurIPS 2026Institute of Software, Chinese AU the Chinese Academy of ScienceInstitute of Software Chinese AcVision-language-action models

PAPO-VLA: Planning-Aware Policy Optimization for Vision-Language-Action Models

PAPO-VLA improves vision-language-action reliability by identifying planning actions via action variation and trajectory outcomes, weighting them by causal importance in policy optimization, and boosting benchmark performance.

Peizheng Guo, Jingyao Wang, Changwen Zheng, Wenwen Qiang

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
78%Highly rated
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NeurIPS 2026U the Chinese Academy of ScienceNankaiGuizhou Power Grid Co., Ltd.Institute of Software, Chinese AInstitute of Software Chinese AcTime series forecasting

Dirichlet-Guided Group Forecasting for Alleviating Over-smoothing in Time Series Forecasting

Dirichlet-Guided Group Forecasting reduces time-series over-smoothing by modeling multi-modal predictive distributions with Dirichlet-guided sampling, improving accuracy, diversity, and dynamical consistency.

Xingyu Zhang, Jingyao Wang, Xin Yu, Zeen Song and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 0/5
83%Must read
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NeurIPS 2026Chinese Academy of SciencesXiaohongshu IncXiaohongshuInstitute of Software, Chinese AInstitute of Software, CASVision-language models

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

Vision-OPD distills a crop-conditioned teacher into a full-image student via on-policy self-distillation to improve fine-grained visual understanding without external teachers or tools. It achieves competitive or superior performance on fine-grained benchmarks against larger open-source, closed-sour

Qianhao Yuan, Jie Lou, XingYu Li, Hongyu Lin and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 5 on Hugging Face

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 0/5