5 papers
Can We Believe AI Peer Review?
Zongrui Yang, Haoyuan Li, Zhongsheng Wang +2
As large language models become widely used in scientific review and manuscript revision, AI scores are increasingly serving as feedback for assessing paper quality and guiding edi…
Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding
Liu Yu, Can Chen, Ping Kuang +3
Large Vision-Language Models (LVLMs) exhibit sophisticated reasoning but remain susceptible to object hallucination. Deviating from the prevailing attention intensity assumption, w…
HoRD: Robust Humanoid Control via History-Conditioned Reinforcement Learning and Online Distillation
Puyue Wang, Jiawei Hu, Yan Gao +7
Humanoid robots can suffer significant performance drops under small changes in dynamics, task specifications, or environment setup. We propose HoRD, a two-stage learning framework…
Causally-Grounded Dual-Path Attention Intervention for Object Hallucination Mitigation in LVLMs
Liu Yu, Zhonghao Chen, Ping Kuang +4
Object hallucination remains a critical challenge in Large Vision-Language Models (LVLMs), where models generate content inconsistent with visual inputs. Existing language-decoder…
Robust Learning of Diffusion Models with Extremely Noisy Conditions
Xin Chen, Gillian Dobbie, Xinyu Wang +3
Conditional diffusion models have the generative controllability by incorporating external conditions. However, their performance significantly degrades with noisy conditions, such…