14 citations · 31 across the 62 of their papers we have counts for
68 papers
SERA: Scale-Equalized Rollout Allocation for Maximum Likelihood Reinforcement Learning
Zihao Chen, Fanxiang Xiong, Hongran Ren +6
Maximum Likelihood Reinforcement Learning (MaxRL) targets prompt-wise log-success and has shown strong performance on reasoning tasks. Under finite rollout budgets, however, the es…
GUITAR: Structured Failure Diagnosis of GUI Agents via State Transitions
Shaoqing Zhang, Kehai Chen, Xuefeng Bai +4
Understanding where and why Graphical User Interface (GUI) agents fail is essential for building more reliable systems, yet current evaluation relies on step accuracy, a metric tha…
Joint Alignment and Distillation for Video Generation via Sample-Guided Distribution Matching
Jiuzhou Lin, Junlong Wu, Fei Zuo +11
Aligning video generative models to human preferences heavily relies on Reinforcement Learning (RL), which suffers from extensive computational overhead. Existing workflows typical…
Hi-TTRL: Regulating Consensus with Hints for Test-Time Reinforcement Learning
Kunbin Xu, Xingzuo Li, Xuefeng Bai +1
Test-time reinforcement learning (TTRL) improves the reasoning capabilities of large language models without labeled data by updating the policy with pseudo-labels constructed thro…
DualAnchor: Preserving Language Priors and Improving Lexical Fidelity in Gloss-Free Sign Language Translation
Hongbin Zhang, Junhao Liu, Xuefeng Bai +3
Recent advances in large language models (LLMs) have led sign language translation (SLT), the task of converting sign-language videos into spoken-language text, to increasingly ado…
SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks
Jinchao Hu, Meizhi Zhong, Kehai Chen +1
Teaching language models to use search tools is not only a question of whether they search, but also of whether they issue good queries. This is especially important in open-domain…
Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey
Bingzheng Qu, Kehai Chen, Xuefeng Bai +1
Recent progress in multimodal large language models (MLLMs) is reshaping video translation from a cascaded pipeline of automatic speech recognition, machine translation, text-to-sp…
User-Aware Active Knowledge Acquisition for Emotional Support Dialogue
Mufan Xu, Kehai Chen, Jiahao Hu +4
Emotional support plays an important role in dialogue systems, and its success depends on adapting to a user's evolving and implicit needs across multi-turn interactions while leve…
CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents
Yihong Tang, Kehai Chen, Liang Yue +2
Recent advancements in Reinforcement Learning (RL), particularly Group Relative Policy Optimization (GRPO), have significantly enhanced the reasoning capabilities of Large Language…
Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning
Hongbin Zhang, Chaozheng Wang, Kehai Chen +4
On-policy self-distillation (OPSD) is an emerging LLM post-training paradigm in which the model serves as its own teacher: conditioned on privileged information such as a reference…
DocOS: Towards Proactive Document-Guided Actions in GUI Agents
Jingjing Liu, Ziye Huang, Zihao Cheng +6
While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric knowledge from pre-training…
MedMemoryBench: Benchmarking Agent Memory in Personalized Healthcare
Yihao Wang, Haoran Xu, Renjie Gu +10
The large-scale deployment of personalized healthcare agents demands memory mechanisms that are exceptionally precise, safe, and capable of long-term clinical tracking. However, ex…
Through the Lens of Character: Resolving Modality-Role Interference in Multimodal Role-Playing Agent
Yihong Tang, Kehai Chen, Xuefeng Bai +1
The advancement of Multimodal Large Language Models (MLLMs) has expanded Role-Playing Agents (RPAs) into visually grounded environments. However, human vision is inherently subject…
Mitigating Multimodal Hallucination via Phase-wise Self-reward
Yu Zhang, Chuyang Sun, Kehai Chen +3
Large Vision-Language Models (LVLMs) still struggle with vision hallucination, where generated responses are inconsistent with the visual input. Existing methods either rely on lar…
Agentic Tool Use in Large Language Models
Jinchao Hu, Meizhi Zhong, Kehai Chen +2
Large language models are increasingly being deployed as autonomous agents yet their real world effectiveness depends on reliable tools for information retrieval, computation and e…
Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck
Hongbin Zhang, Kehai Chen, Xuefen Bai +4
Large language models (LLMs) have become a standard for multilingual evaluation, yet they exhibit a severe systematic translationese bias. In this paper, translationese bias is cha…
Beyond Token-Level Policy Gradients for Complex Reasoning with Large Language Models
Mufan Xu, Kehai Chen, Xuefeng Bai +4
Existing policy-gradient methods for auto-regressive language models typically select subsequent tokens one at a time as actions in the policy. While effective for many generation…
Beyond Unimodal Shortcuts: MLLMs as Cross-Modal Reasoners for Grounded Named Entity Recognition
Jinlong Ma, Yu Zhang, Xuefeng Bai +5
Grounded Multimodal Named Entity Recognition (GMNER) aims to extract text-based entities, assign them semantic categories, and ground them to corresponding visual regions. In this…
Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structure
Zirui Li, Xuefeng Bai, Kehai Chen +4
Latent or continuous chain-of-thought methods replace explicit textual rationales with a number of internal latent steps, but these intermediate computations are difficult to evalu…
Instruction Anchor: Dissecting the Mechanistic Dynamics of Modality Arbitration
Yu Zhang, Mufan Xu, Xuefeng Bai +4
Modality following is the ability to selectively leverage multimodal contexts based on user instructions. It is fundamental to the safety and reliability of multimodal large langua…
Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance
Yingjie Zhu, Xuefeng Bai, Kehai Chen +4
Reasoning over table images remains challenging for Large Vision-Language Models (LVLMs) due to complex layouts and tightly coupled structure-content information. Existing solution…
VC-Bench: Pioneering the Video Connecting Benchmark with a Dataset and Evaluation Metrics
Zhiyu Yin, Zhipeng Liu, Kehai Chen +5
While current video generation focuses on text or image conditions, practical applications like video editing and vlogging often need to seamlessly connect separate clips. In our w…
Character-R1: Enhancing Role-Aware Reasoning in Role-Playing Agents via RLVR
Yihong Tang, Kehai Chen, Xuefeng Bai +4
Current role-playing agents (RPAs) are typically constructed by imitating surface-level behaviors, but this approach lacks internal cognitive consistency, often causing out-of-char…
Beyond Rigid: Benchmarking Non-Rigid Video Editing
Bingzheng Qu, Xuefeng Bai, Kehai Chen +1
As video generation models are increasingly expected to manipulate physical dynamics, there is a growing need to move evaluation beyond appearance fidelity and semantic alignment.…