1 citations · 3 across the 21 of their papers we have counts for
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GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs
Meixiu Long, Duolin Sun, Dan Yang +12
Large Language Models (LLMs) have emerged as powerful tools for passage reranking in information retrieval, leveraging their superior reasoning capabilities to address the limitati…
Scaling over Scaling: Exploring Test-Time Scaling Plateau in Large Reasoning Models
Jian Wang, Boyan Zhu, Chak Tou Leong +2
Large reasoning models (LRMs) have exhibited the capacity of enhancing reasoning performance via internal test-time scaling. Building upon this, a promising direction is to further…
SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution
Hanlin Wang, Chak Tou Leong, Jiashuo Wang +2
Reinforcement learning (RL) holds significant promise for training LLM agents to handle complex, goal-oriented tasks that require multi-step interactions with external environments…
Reasoning Beyond Language: A Comprehensive Survey on Latent Chain-of-Thought Reasoning
Xinghao Chen, Anhao Zhao, Heming Xia +7
Large Language Models (LLMs) have shown impressive performance on complex tasks through Chain-of-Thought (CoT) reasoning. However, conventional CoT relies on explicitly verbalized…
Towards Harmless Multimodal Assistants with Blind Preference Optimization
Yongqi Li, Lu Yang, Jian Wang +3
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction. Given the extensive applications of MLLM…
Integrating Chain-of-Thought for Multimodal Alignment: A Study on 3D Vision-Language Learning
Yanjun Chen, Yirong Sun, Xinghao Chen +4
Chain-of-Thought (CoT) reasoning has proven effective in natural language tasks but remains underexplored in multimodal alignment. This study investigates its integration into 3D v…
STeCa: Step-level Trajectory Calibration for LLM Agent Learning
Hanlin Wang, Jian Wang, Chak Tou Leong +1
Large language model (LLM)-based agents have shown promise in tackling complex tasks by interacting dynamically with the environment. Existing work primarily focuses on behavior cl…
Why Safeguarded Ships Run Aground? Aligned Large Language Models' Safety Mechanisms Tend to Be Anchored in The Template Region
Chak Tou Leong, Qingyu Yin, Jian Wang +1
The safety alignment of large language models (LLMs) remains vulnerable, as their initial behavior can be easily jailbroken by even relatively simple attacks. Since infilling a fix…
Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors
Jian Wang, Yinpei Dai, Yichi Zhang +3
Intelligent tutoring agents powered by large language models (LLMs) have been increasingly explored to deliver personalized knowledge in areas such as language learning and science…