1 citations · 1 across the 5 of their papers we have counts for
10 papers
Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
Qixin Zhang, Yan Sun, Can Jin +5
In this paper, we present two effective policy learning algorithms for multi-agent online coordination(MA-OC) problem. The first one, \texttt{MA-SPL}, not only can achieve the opti…
EchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models
Botai Yuan, Yutian Zhou, Yingjie Wang +9
Recent benchmarks for medical Large Vision-Language Models (LVLMs) emphasize leaderboard accuracy, overlooking reliability and safety. We study sycophancy -- models' tendency to un…
Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval
Rong-Cheng Tu, Wenhao Sun, Hanzhe You +4
Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve target images given a compositional query, consisting of a reference image and a modifying text-without relying on anno…
MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval
Rong-Cheng Tu, Zhao Jin, Jingyi Liao +4
Existing Zero-Shot Composed Image Retrieval (ZS-CIR) methods typically train adapters that convert reference images into pseudo-text tokens, which are concatenated with the modifyi…
R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO
Huanjin Yao, Qixiang Yin, Jingyi Zhang +8
In this work, we aim to incentivize the reasoning ability of Multimodal Large Language Models (MLLMs) via reinforcement learning (RL) and develop an effective approach that mitigat…
Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization
Haotian Luo, Haiying He, Yibo Wang +6
Recently, long-thought reasoning models achieve strong performance on complex reasoning tasks, but often incur substantial inference overhead, making efficiency a critical concern.…