4 citations · 7 across the 38 of their papers we have counts for
41 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…
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…
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…
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…
SAT: Balancing Reasoning Accuracy and Efficiency with Stepwise Adaptive Thinking
Weiyang Huang, Xuefeng Bai, Kehai Chen +4
Large Reasoning Models (LRMs) have revolutionized complex problem-solving, yet they exhibit a pervasive "overthinking", generating unnecessarily long reasoning chains. While curren…
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…
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…
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.…
Evaluating and Improving Cultural Awareness of Reward Models for LLM Alignment
Hongbin Zhang, Kehai Chen, Xuefeng Bai +2
Reward models (RMs) are crucial for aligning large language models (LLMs) with diverse cultures. Consequently, evaluating their cultural awareness is essential for further advancin…
Culture In a Frame: CB as a Comic-Based Benchmark for Multimodal Culturally Awareness
Yuchen Song, Andong Chen, Wenxin Zhu +4
Cultural awareness capabilities have emerged as a critical capability for Multimodal Large Language Models (MLLMs). However, current benchmarks lack progressed difficulty in their…
Beyond the Vision Encoder: Identifying and Mitigating Spatial Bias in Large Vision-Language Models
Yingjie Zhu, Xuefeng Bai, Kehai Chen +6
Large Vision-Language Models (LVLMs) have achieved remarkable success across a wide range of multimodal tasks, yet their robustness to spatial variations remains insufficiently und…
HITSZ's End-To-End Speech Translation Systems Combining Sequence-to-Sequence Auto Speech Recognition Model and Indic Large Language Model for IWSLT 2025 in Indic Track
Xuchen Wei, Yangxin Wu, Yaoyin Zhang +4
This paper presents HITSZ's submission for the IWSLT 2025 Indic track, focusing on speech-to-text translation (ST) for English-to-Indic and Indic-to-English language pairs. To enha…
The Hidden Link Between RLHF and Contrastive Learning
Xufei Lv, Kehai Chen, Haoyuan Sun +3
Alignment of large language models (LLMs) with human values has recently garnered significant attention, with prominent examples including the canonical yet costly Reinforcement Le…
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Yuchen Wang, Xuefeng Bai, Xiucheng Li +3
Adapting vision-language models (VLMs) to downstream tasks with pseudolabels has gained increasing attention. A major obstacle is that the pseudolabels generated by VLMs tend to be…
Evaluating and Steering Modality Preferences in Multimodal Large Language Model
Yu Zhang, Jinlong Ma, Yongshuai Hou +5
Multi-modal large language models (MLLMs) have achieved remarkable success on complex multi-modal tasks. However, it remains insufficiently explored whether they exhibit $\textbf{m…
MoK-RAG: Mixture of Knowledge Paths Enhanced Retrieval-Augmented Generation for Embodied AI Environments
Zhengsheng Guo, Linwei Zheng, Xinyang Chen +3
While human cognition inherently retrieves information from diverse and specialized knowledge sources during decision-making processes, current Retrieval-Augmented Generation (RAG)…
Adaptive Inner Speech-Text Alignment for LLM-based Speech Translation
Henglyu Liu, Andong Chen, Kehai Chen +4
Recent advancement of large language models (LLMs) has led to significant breakthroughs across various tasks, laying the foundation for the development of LLM-based speech translat…