Good Papers

Showing papers from The Hong Kong University of Science and Technology (Guangzhou) Show all papers

57%Worth a look
?Worth a lookVote to see the score

Correction Space Steering for Hallucination Mitigation in Large Vision-Language Models

Songbo Yang, Shuliang Liu, Sihang Jia, Xuming Hu

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
57%Worth a look
?Worth a lookVote to see the score

GeoPano: Towards Geometrically Accurate Panoramic 3D Reconstruction from a Single Panorama

Jing OU, Zidong Cao, Liaoyuan Fan, Zhuoxiao Li and 6 more

Sydney Poster Session 3, Wed, Dec 9, 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.

57%Worth a look
?Worth a lookVote to see the score

Machine Unlearning in Diffusion LLMs

Yili Wang, Yijie Xu, Lu Dai, Tairan Huang and 4 more

Sydney Poster Session 4, Wed, Dec 9, 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

Bayesian Causal Experimental Design for CATE Estimation under Noncompliance

Erdun Gao, Yuanyuan Wang, Liang Zhang, Yuhang Liu and 3 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
67%Highly rated
?Highly ratedVote to see the score

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering with Generative Optimization

Dapeng Jiang, Yizhe Chi, Kaisen Yang, Tianwei Luo and 18 more

Sydney Poster Session 5, Thu, Dec 10, 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
67%Highly rated
?Highly ratedVote to see the score

CitySTAR: Agent-Driven Structured and Topology-Aware Reasoning for Open-Vocabulary Urban 3D Grounding

Shuai Zhang, Hongye Hou, qinghe liu, Zhuoxiao Li and 4 more

Sydney Poster Session 2, Tue, Dec 8, 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
45%Niche pick
?Niche pickVote to see the score

The Alternation Depth Principle for Neural Operator Design

Haoze Song, Zhilu Lai, Wei Wang

Sydney Poster Session 4, Wed, Dec 9, 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

PipeFSDP: Efficient Pipeline Parallel under Fully Sharded Data Parallel for Large Language Model Training

Xinglin Pan, Mingji Han, Penghao Zhao, Lin Zheng and 4 more

Sydney Poster Session 3, Wed, Dec 9, 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.

67%Highly rated
?Highly ratedVote to see the score

Taming CoT Obfuscation in VLMs: From Mechanistic Evidence to Activation-Level Enforcement

Xutao Mao, Jianing Zhu, Jinman Zhao, Tongliang Liu and 3 more

Sydney Poster Session 2, Tue, Dec 8, 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 1/5
medium 1/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Grounding 3D Affordance from Human-Object-Interaction Videos via Multimodal Large Language Model

Hanqing Wang, Mingyu Liu, Xiaoyu Chen, Chengwei MA and 9 more

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
57%Worth a look
?Worth a lookVote to see the score

Train at the Moving Edge: Rollout-Efficient RL for Large Reasoning Models

Jiahao Wu, Ning Lu, Shengcai Liu, Kun Wang and 5 more

Sydney Poster Session 3, Wed, Dec 9, 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

Multimodal Context-Aware Human Motion Generation with Language, Vision, and Object

Junyu Shi, Yong Sun, Zhiyuan Zhang, Lijiang LIU and 3 more

Sydney Poster Session 4, Wed, Dec 9, 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
67%Highly rated
?Highly ratedVote to see the score

Less Evidence, Better Answering: Gain-Aware Minimal Evidence Subset Selection for Medical QA

Songyue Guo, Zhao CHEN, Caleb C Cao, Lei Chen

Sydney Poster Session 5, Thu, Dec 10, 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
69%Highly rated
?Highly ratedVote to see the score

Is Your LLM-as-a-Recommender Agent Trustable? LLMs' Recommendation is Easily Hacked by Biases (Preferences)

Zichen TANG, Zirui Zhang, Qian Wang, Zhenheng Tang and 2 more

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

– ReadersNo votes yet
3/20 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: 3 of 20 reviewers recommend it
lenient 2/5
medium 1/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score

Horizon-Stream: Long-Horizon Attention for Streaming 3D Reconstruction

Chong Cheng, Peilin Tao, Nanjie Yao, Guanzhi Ding and 8 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

Rare Disease Diagnosis Agent with Decoupled Workflows and Knowledge-Driven Self-Evaluation

Yunlu Yan, Yawen Huang, Xian Wu, Lei Zhu

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
57%Worth a look
?Worth a lookVote to see the score

Reinforced Evidence-Aware Long Video Understanding

Yuan Xie, Tianshui Chen, Deyu Zhou, Lionel Ni

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · 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.

57%Worth a look
?Worth a lookVote to see the score

MGMem: An Efficient, Deterministic, and Provenance-Preserving Framework for Long-Horizon Agent Memory

Junhong Huang, Xin Tong, Jun Xia

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
57%Worth a look
?Worth a lookVote to see the score

Diving-R1: Empowering Multimodal LLMs with Traceable Progressive Reasoning for Interpretable Diving Action Quality Assessment

Kaishen Yuan, Yuting Zhang, Bohao Xing, Wenshuo Chen and 4 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
45%Niche pick
?Niche pickVote to see the score

Collapse Hunter: Tackling the Dimensional Degeneration in Generative Ranking

Haoran Xin, Junwei Pan, Yongqi Zhou, Tianqu Zhuang and 7 more

Sydney Poster Session 1, Tue, Dec 8, 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
57%Worth a look
?Worth a lookVote to see the score

DiffCool: Label-Free Synthesis of Chip-Tailored Heat Sinks via Thermal-Aware Diffusion

Siyuan Liang, Zixiao Wang, Chenghan Wang, Shanyi Li and 6 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
57%Worth a look
?Worth a lookVote to see the score

Two Drifts, One Principle: Conflict-Aware Spectral Consolidation for Multimodal Continual Learning

Haiyi Zhang, Qianyi Cai, Hanqing Wang, Zilin Wang and 6 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

Static-to-Dynamic: Animating Still Mattes via Generative Motion for Video Matting

Suqi Song, Jiaqi Xu, Jialuo He, Renjing Pei 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
57%Worth a look
?Worth a lookVote to see the score

Block-OBS-GS: Exact Per-Block Joint Brain Surgery with Gauss–Seidel Refinement for LLM Pruning

Yuwen Huang, Xiang Pan

Sydney Poster Session 4, Wed, Dec 9, 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

Curvature-Guided Parameter Initialization for Multi-Task Learning

Linxiao Cao, Zhipeng Zhou, Xutao Huang, Min Zhou and 1 more

Sydney Poster Session 1, Tue, Dec 8, 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.

57%Worth a look
?Worth a lookVote to see the score

Pose-Free Feed-Forward 3D Inpainting via Learnable Mask Attention and Support Token Refinement

Jingyi Pan, Dan Xu, Qiong Luo

Sydney Poster Session 3, Wed, Dec 9, 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

ClinStab: Stability-Oriented Learning for Medical Time Series via Dual-Stream Alignment

Songning Lai, Haoxuan Xu, Yi Liu, Wenshuo Chen and 4 more

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
57%Worth a look
?Worth a lookVote to see the score

Revisiting Autoregressive GCNs for Vehicle Routing Problems

Zhipeng Zhong, Junquan Huang, Yu Huang, Boyuan Zheng and 5 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.

45%Niche pick
?Niche pickVote to see the score

The Cost of Mismatch: Noise Amplification in Zeroth-Order Reinforcement Learning

Lianmin Chen, Junbin Qiu, Chenxing Wei, Yao SHU 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.

57%Worth a look
?Worth a lookVote to see the score

Taking Low-Rank LLM Compression a Step Further: A Global Perspective with Fused Inference

Xinhao Huang, Yuqiang He, Zeyi Wen

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · 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

Route-Consistent Adaptation for Stable Quantization of Mixture-of-Experts Models with Theoretical Guarantees

Longteng Zhang, Sen Wu, Qiang Wang, Shaohuai Shi and 1 more

Sydney Poster Session 4, Wed, Dec 9, 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

Near-Optimal Learning in Parametric Bandits with Action-Dependent Coarsened Feedback

Zhuohua Li, MAOLI LIU, Yuwen Huang, Cheng Wen and 4 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.

67%Highly rated
?Highly ratedVote to see the score

Dodge-It: Learning Collision-Aware VLA Models for Robotic Manipulation

Jiawei Feng, Chuzhao Huang, Xinli Xu, Yingcong Chen

Sydney Poster Session 4, Wed, Dec 9, 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

Toward Efficient Reasoning of Large Language Models via Latent Concept-Pyramid Modeling

Sijia Chen, Ningxin Su

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
57%Worth a look
?Worth a lookVote to see the score

UltraDiff:Transferring High-Fidelity Priors to Compressed Latent Spaces for High-resolution Image Generation

Jingjing Ren, Haitian Zheng, Haoyu Chen, Connelly Barnes and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · 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

Motion Forcing: Decoupling Ego and Object Motion via Sparse Inputs for Structured Video Generation

Tianshuo Xu, ZhiFei Chen, Leyi Wu, Hao LU and 1 more

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

MAPS: Margin-Aware Priors and Verifier-Guided Search for Embodied Planning

XIN Li, Junquan Huang, Xujia Li, Lei Chen

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 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
83%Must read
?Must readVote to see the score

Strengthening LLMs for Tabular Prediction with Structural Priors

PRPO incorporates column-permutation invariance into LLM post-training via label-preserving permutations and two-level advantage estimation, enabling an 8B model to match specialized tabular baselines and outperform 685B reasoning LLMs by up to 53%.

Pengxiang Cai, Zihao Gao, Wanchen Lian, Guocong Li and 1 more

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

– ReadersNo votes yet
13/20 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: 13 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 3/5
78%Highly rated
?Highly ratedVote to see the score

Ask, Answer, and Detect: Role-Playing LLMs for Personality Detection with Question-Conditioned Mixture-of-Experts

ROME uses role-playing LLMs to generate questionnaire answers from posts, then routes them via mixture-of-experts to improve personality detection and mitigate label scarcity.

Yifan Lyu, Liang Zhang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 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
78%Highly rated
?Highly ratedVote to see the score

Reformulating Neural Operators in $d+1$ Dimensions for Embedding Evolution

Reformulating neural operators in d+1 dimensions via auxiliary embedding evolution achieves lowest relative L2 error across benchmarks without brute-force scaling.

Haoze Song, Zhihao Li, Xiaobo Zhang, Zecheng Gan and 2 more

Sydney Poster Session 3, Wed, Dec 9, 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 2/5
medium 7/10
strict 2/5
80%Must read
?Must readVote to see the score

Robust Conditional Conformal Prediction via Branched Normalizing Flow

Branched Normalizing Flow bounds conditional invalidity via Wasserstein distance and improves robust conditional coverage under distribution shift.

Rui Xu, Xingyuan Chen, Wenxing Huang, Minxuan Huang and 3 more

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

– ReadersNo votes yet
12/20 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: 12 of 20 reviewers recommend it
lenient 2/5
medium 9/10
strict 1/5
78%Highly rated
?Highly ratedVote to see the score

Geometry-Calibrated Conformal Abstention for Language Models

Conformal Abstention uses geometry-calibrated confidence to decide abstention with finite-sample correctness guarantees, achieving 75% conditional correctness.

Rui Xu, Yi Chen, Sihong Xie, Hui Xiong

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.

88%Must read
?Must readVote to see the score

AdapToPASS: Ambiguity-aware Adaptive Spherical Transformer for Panoramic Semantic Segmentation

AdapToPASS is a bio-inspired spherical transformer that adaptively models contextual and geometric ambiguities to achieve robust panoramic semantic segmentation, outperforming state-of-the-art methods by up to 18.77% relative mIoU under unseen spherical transformations.

Soumyaratna Debnath, weiming zhang, Shriram Damodaran, Dingwen Xiao and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– 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.

71%Highly rated
?Highly ratedVote to see the score

UniGS: Unified Geometry-Aware Gaussian Splatting for Multimodal Rendering

UniGS proposes a unified geometry-aware Gaussian Splatting framework that simultaneously renders RGB, depth, normals, and semantics with state-of-the-art multimodal reconstruction accuracy.

Yusen XIE, Zhenmin Huang, Jianhao Jiao, Dimitrios Kanoulas and 1 more

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

– ReadersNo votes yet
6/20 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: 6 of 20 reviewers recommend it
lenient 2/5
medium 3/10
strict 1/5
89%Must read
?Must readVote to see the score

From Table to Cell: Attention for Better Reasoning with TABALIGN

TABALIGN improves multi-step table reasoning by pairing diffusion planners generating binary cell masks with attention verifiers, raising accuracy 15.76 points and accelerating execution 44.64%.

Tung Sum Thomas Kwok, Zeyong Zhang, Xinyu Wang, Chunhe Wang and 5 more

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

– ReadersNo votes yet
16/20 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: 16 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 3/5
71%Highly rated
?Highly ratedVote to see the score

RotMoLE: Enhancing Mixture of Low-Rank Experts through Rotational Gating Mechanism

RotMoLE adds a rotation gate to MoE-LoRA experts that rotates rather than merely scaling selected experts, improving specialization and performance on multi-task and multilingual benchmarks.

Mengyang Sun, MaoChuan Dou, Tao Feng, Dan Zhang and 4 more

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

– ReadersNo votes yet
6/20 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: 6 of 20 reviewers recommend it
lenient 4/5
medium 2/10
strict 0/5
78%Highly rated
?Highly ratedVote to see the score

Delve into the Applicability of Advanced Optimizers for Multi-Task Learning

Advanced optimizers weaken multi-task learning because instant gradients barely affect updates, so the APT framework with adaptive momentum and Muon direction preservation improves results across four datasets.

Zhipeng Zhou, Linxiao Cao, Yiming Cao, Pengcheng Wu and 2 more

Sydney Poster Session 3, Wed, Dec 9, 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 2/5
medium 8/10
strict 1/5
71%Highly rated
?Highly ratedVote to see the score

PDF-HR: Pose Distance Fields for Humanoid Robots

PDF-HR learns continuous, differentiable pose distance fields from retargeted humanoid motions to score pose plausibility, substantially improving tracking, mimicry, and retargeting baselines.

Yi Gu, Yukang Gao, Yangchen Zhou, Xingyu Chen and 6 more

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

– ReadersNo votes yet
7/20 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: 7 of 20 reviewers recommend it
lenient 5/5
medium 2/10
strict 0/5
83%Must read
?Must readVote to see the score

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Reward Models

CodeScaler uses a reward model to scale code LLM training and inference without test cases, improving benchmarks by up to 14.64 points and cutting latency tenfold.

Xiao Zhu, Xinyu Zhou, Boyu Zhu, Hanxu Hu and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 24 on Hugging Face · Code ★ 50

– ReadersNo votes yet
13/20 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: 13 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 2/5
80%Must read
?Must readVote to see the score

HumanoidArena: Benchmarking Egocentric Hierarchical Whole-body Learning

HumanoidArena benchmarks egocentric hierarchical whole-body learning via seven leg-critical tasks, finding policies solve diverse interactions but cross-tracker transfer remains fragile.

Taowen Wang, Zikang Xie, Bin Yang, Yunheng Wang and 12 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 18 on Hugging Face

– ReadersNo votes yet
12/20 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: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
83%Must read
?Must readVote to see the score

Next Forcing: Causal World Modeling with Multi-Chunk Prediction

Next Forcing uses multi-chunk prediction to accelerate convergence 2.3x, boost high-frame-rate accuracy 93.1%, and double inference speed for world models.

Gangwei Xu, Qihang Zhang, Jiaming Zhou, Xing Zhu and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 8 on Hugging Face · Code ★ 136

– ReadersNo votes yet
13/20 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: 13 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 2/5
76%Highly rated
?Highly ratedVote to see the score

Seg3DParts: Segmentation-Grounded Controllable Part-Level 3D Generation

Seg3DParts uses segmentation-grounded generation with structured cross-part interaction to produce controllable, coherent part-level 3D meshes from single images while introducing the PartObjectNet dataset.

Jiantao Lin, Meixi Chen, Yingjie Xu, Chenbo FU and 4 more

Sydney Poster Session 5, Thu, Dec 10, 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 5/5
medium 4/10
strict 1/5
74%Highly rated
?Highly ratedVote to see the score

XDecomposer: Learning Prior-Free Set Decomposition for Multiphase X-ray Diffraction

XDecomposer learns prior-free multiphase X-ray diffraction decomposition as set prediction to identify constituent phases and proportions without candidate lists. It improves reconstruction accuracy and phase identification across simulated and experimental datasets.

Hanyu Gao, Bin Cao, YUNYUE SU, Tong-yi Zhang and 1 more

Sydney Poster Session 6, Thu, Dec 10, 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
78%Highly rated
?Highly ratedVote to see the score

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving

IRR-Drive uses adaptive multimodal text and BEV reflection to self-correct driving intentions before trajectory generation, achieving state-of-the-art NAVSIM results.

Zisheng Chen, Yuping Qiu, Jianhua Han, Tao Tang and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 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
86%Must read
?Must readVote to see the score

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

EvoMemBench benchmarks LLM agent memory via self-evolving scope and content axes, finding no universal memory method and that long-context baselines remain competitive.

Yuyao Wang, Zhongjian Zhang, Mo Chi, Kaichi Yu and 6 more

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

– 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 7/10
strict 3/5
86%Must read
?Must readVote to see the score

The Illusion of Multi-Agent Advantage

Automatic multi-agent systems consistently underperform single-agent chain-of-thought self-consistency despite up to 10x cost, revealing automated architectures suffer from bloat and misaligned complexity rather than true multi-agent benefits.

Prathyusha Jwalapuram, Hehai Lin, Chuyuan Li, Fangkai Jiao and 6 more

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

– 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
89%Must read
?Must readVote to see the score

PepSpecBench: A Unified Evaluation Benchmark for Peptide Tandem Mass Spectrometry Prediction

PepSpecBench standardizes peptide MS/MS prediction evaluation via strict backbone-disjoint splits, unified outputs, multi-species tests, and robustness probes, revealing hidden model limitations.

Zhiwen Yang, Pan Liu, yifan Li, Yunhua Zhong and 1 more

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

– ReadersNo votes yet
16/20 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: 16 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 2/5
80%Must read
?Must readVote to see the score

ColorConceptBench: A Benchmark for Probabilistic Color-Concept Understanding in Text-to-Image Models

ColorConceptBench evaluates text-to-image models on probabilistic color associations for 1,281 implicit concepts, revealing substantial performance gaps and insensitivity to abstract semantics.

Chenxi Ruan, Yihan Hou, Yu Xiao, Guosheng Hu and 1 more

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

– ReadersNo votes yet
12/20 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: 12 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 2/5
89%Must read
?Must readVote to see the score

OmniTraffic: A Controllable Generation Pipeline and Benchmark for Spatio-Temporal Traffic Reasoning

OmniTraffic introduces a controllable 3D traffic generation pipeline and benchmark with 8M VQA samples for spatio-temporal reasoning, revealing large model gaps and improved real-world performance via simulated fine-tuning.

Maonan Wang, Zhengyan Huang, Kemou Jiang, Yuhang Fu and 12 more

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

– ReadersNo votes yet
16/20 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: 16 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 3/5