Good Papers

Showing papers from City University of Hong Kong (Dongguan) Show all papers

67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026City University of Hong KongNanyang TechnologicalU Hong KongHarbin Institute of TechnologyCity University of Hong KongVision-language models

MedVIGOR: Visual Evidence Internalization for Observation-Driven Reasoning in Medical VLMs

Yuan Wu, Jiayu Qian, Sipeng Wu, Songpan Gao and 5 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 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
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Computer Vision Center, UniversiUniversitat Autónoma de BarcelonNankaiComputer Vision Center BarcelonaCity University of Hong Kong3D generation

DiDE: Direct Injection with Color-Texture DEcoupling for 3D Stylization

Tao Wu, Alexandra Gomez-Villa, Senmao Li, Yaxing Wang and 2 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 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
78%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026City University of Hong KongImperial College LondonCity University of Hong KongU OxfordAstraZenecaTime series foundation models

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons

A parameter-efficient plugin extends frozen 10-second ECG foundation models to long, variable-length recordings via compatible long-sequence processing and semantically informed temporal modeling, outperforming sliding-window and pooling baselines.

Wei Tang, Jinpei Han, Kangning Cui, Mattia Carletti and 9 more

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

– ReadersNo votes yet
11/20 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: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5
92%Must read
?Must readVote to see the score
NeurIPS 2026DukeDepartment of Computer Science, City University of Hong KongCarnegie MellonDuke University, DukeEfficient inference & serving

LowRankArena: A Standardized Evaluation Platform for SVD-Based LLM Compression

LowRankArena standardizes SVD-based LLM compression evaluation and reveals that method rankings and speedups depend heavily on backbone and workload under aligned protocols.

Zishan Shao, Lixun Zhang, Kangning Cui, Wenhao Wu and 9 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 1 on Hugging Face

– ReadersNo votes yet
19/20 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: 19 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 4/5
91%Must read
?Must readVote to see the score
NeurIPS 2026City University of Hong KongCity University of Hong KongCity University of Hong Kong3D vision & reconstruction

One World, Dual Timeline: Decoupled Spatio-Temporal Gaussian Scene Graph for 4D Cooperative Driving Reconstruction

DUST uses decoupled dual-timeline Gaussian scene graphs for asynchronous vehicle-infrastructure 4D reconstruction, cutting ghosting to boost dynamic-area PSNR by 3.2 dB.

Yulong Chen, Xiaoyun Dong, Haoyu Zhang, Zongxian Yang and 5 more

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

– ReadersNo votes yet
17/20 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: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026U Science and Technology of ChinU the Chinese Academy of ScienceCity University of Hong KongTsinghuaZhejiangEmbodied agents

MineEvolve: Self-Evolution with Accumulated Knowledge for Long-Horizon Embodied Minecraft Agents

MineEvolve converts Minecraft execution feedback into structured skills and remedies via Monitor, Inducer, Curator, and Adaptor, improving long-horizon agent performance across planners.

Zhengwei Xie, Zhisheng Chen, Ziyan Weng, Jinhan Li and 6 more

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

– 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 4/5
medium 5/10
strict 0/5