Good Papers

Showing papers from Shanghai AI Lab Show all papers

67%Highly rated
?Highly ratedVote to see the score

Hydra-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor Control

Jinhao Zhang, Zhexuan Zhou, Huizhe Li, Yichen Lai and 4 more

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

– ReadersNo votes yet
2/20 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: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

LG-Bench: A Graph-Structured Evaluation Benchmark for Life Science

Lu Sun, Xiangyi Zhang, Xiangyang Zhu, Zijian Chen and 3 more

Sydney Poster Session 2, Tue, Dec 8, 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

VUM: Visual Unified Models for Image Generation and Perception

ZiDong Wang, Yiyuan Zhang, Xiaoyu Yue, Xiangyuan Xue and 3 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
88%Must read
?Must readVote to see the score

PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control

PAGER closes the semantic-execution gap for point-precise geometric GUI control via dependency-structured planning and pixel-level execution, achieving 4.1x higher task success than general baselines.

Jingxuan Wei, Xi Bai, Shan Liu, caijun jia and 7 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 15 on Hugging Face · Code ★ 3

– ReadersNo votes yet
15/20 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: 15 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 3/5
76%Highly rated
?Highly ratedVote to see the score

AgenticOCR: Parsing Only What You Need for Efficient Retrieval-Augmented Generation

AgenticOCR transforms OCR into query-driven, on-demand extraction to selectively parse document regions, improving visual RAG efficiency and accuracy over page-level chunking.

Zhengren Wang, Dongsheng Ma, Huaping Zhong, Jiayu Li and 5 more

Sydney Poster Session 6, Thu, Dec 10, 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
76%Highly rated
?Highly ratedVote to see the score

Train the Agent, Not the Expert: Learning to Harness Heterogeneous Experts for Multi-Turn Visual Reasoning

VisHarness trains a visual agent to orchestrate heterogeneous experts for multi-turn reasoning, achieving strong results on segmentation, detection, and counting tasks.

Yaowu Fan, Tao Han, Dazhao Du, Jinhua Ma and 1 more

Sydney Poster Session 6, Thu, Dec 10, 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 4/5
medium 6/10
strict 0/5
76%Highly rated
?Highly ratedVote to see the score

StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction

StraTA introduces trajectory-level strategies into agentic reinforcement learning via hierarchical rollout training, improving long-horizon decision-making and reaching 93.1% on ALFWorld.

Xiangyuan Xue, Yifan Zhou, ZiDong Wang, Shengji Tang and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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 4/5
medium 5/10
strict 1/5