14 citations · 31 across the 62 of their papers we have counts for
24 papers · 1 filter
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…
Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents
Yihong Tang, Kehai Chen, Liang Yue +11
With the rise of large language models (LLMs), LLM agents capable of autonomous reasoning, planning, and executing complex tasks have become a frontier in artificial intelligence.…
LoCoT2V-Bench: Benchmarking Long-Form and Complex Text-to-Video Generation
Xiangqing Zheng, Chengyue Wu, Kehai Chen +1
Recent advances in text-to-video generation have achieved impressive performance on short clips, yet evaluating long-form generation under complex textual inputs remains a signific…
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…
MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching
Liang Yue, Yihong Tang, Kehai Chen +2
Instruction fine-tuning is crucial in NLP tasks, enhancing pretrained models' instruction-following capabilities and task-specific performance. However, obtaining high-quality fine…
ORPP: Self-Optimizing Role-playing Prompts to Enhance Language Model Capabilities
Yifan Duan, Yihong Tang, Kehai Chen +2
High-quality prompts are crucial for eliciting outstanding performance from large language models (LLMs) on complex tasks. Existing research has explored model-driven strategies fo…
Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning
Yihong Tang, Kehai Chen, Muyun Yang +4
The advancement of Large Language Models (LLMs) has spurred significant interest in Role-Playing Agents (RPAs) for applications such as emotional companionship and virtual interact…
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…
XBOUND: Exploring Capability Boundaries of Device-Control Agents at the State Level
Shaoqing Zhang, Kehai Chen, Zhuosheng Zhang +4
Recent advancements in vision-language models have increased interest in Device-Control Agents (DC agents) for managing graphical user interfaces (GUIs). With the growing complexit…
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…
Memory-augmented Query Reconstruction for LLM-based Knowledge Graph Reasoning
Mufan Xu, Gewen Liang, Kehai Chen +5
Large language models (LLMs) have achieved remarkable performance on knowledge graph question answering (KGQA) tasks by planning and interacting with knowledge graphs. However, exi…
Efficient Safety Alignment of Large Language Models via Preference Re-ranking and Representation-based Reward Modeling
Qiyuan Deng, Xuefeng Bai, Kehai Chen +3
Reinforcement Learning (RL) algorithms for safety alignment of Large Language Models (LLMs), such as Direct Preference Optimization (DPO), encounter the challenge of distribution s…
XIFBench: Evaluating Large Language Models on Multilingual Instruction Following
Zhenyu Li, Kehai Chen, Yunfei Long +5
Large Language Models (LLMs) have demonstrated remarkable instruction-following capabilities across various applications. However, their performance in multilingual settings lacks…
Generator-Assistant Stepwise Rollback Framework for Large Language Model Agent
Xingzuo Li, Kehai Chen, Yunfei Long +3
Large language model (LLM) agents typically adopt a step-by-step reasoning framework, in which they interleave the processes of thinking and acting to accomplish the given task. Ho…
The Rise of Darkness: Safety-Utility Trade-Offs in Role-Playing Dialogue Agents
Yihong Tang, Kehai Chen, Xuefeng Bai +4
Large Language Models (LLMs) have made remarkable advances in role-playing dialogue agents, demonstrating their utility in character simulations. However, it remains challenging fo…
Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis
Andong Chen, Yuchen Song, Wenxin Zhu +4
The o1-Like LLMs are transforming AI by simulating human cognitive processes, but their performance in multilingual machine translation (MMT) remains underexplored. This study exam…
The Power of Personality: A Human Simulation Perspective to Investigate Large Language Model Agents
Yifan Duan, Yihong Tang, Xuefeng Bai +3
Large language models (LLMs) excel in both closed tasks (including problem-solving, and code generation) and open tasks (including creative writing), yet existing explanations for…
A Survey: Spatiotemporal Consistency in Video Generation
Zhiyu Yin, Kehai Chen, Xuefeng Bai +7
Video generation aims to produce temporally coherent sequences of visual frames, representing a pivotal advancement in Artificial Intelligence Generated Content (AIGC). Compared to…
Exploring the Translation Mechanism of Large Language Models
Hongbin Zhang, Kehai Chen, Xuefeng Bai +3
While large language models (LLMs) demonstrate remarkable success in multilingual translation, their internal core translation mechanisms, even at the fundamental word level, remai…
Make Imagination Clearer! Stable Diffusion-based Visual Imagination for Multimodal Machine Translation
Andong Chen, Yuchen Song, Kehai Chen +3
Visual information has been introduced for enhancing machine translation (MT), and its effectiveness heavily relies on the availability of large amounts of bilingual parallel sente…