1 citations · 3 across the 21 of their papers we have counts for
22 papers
Deep Image Prototype Learning with Geometric Heat-Kernel Priors
Jiarui Xing, Tal Zeevi, Nian Wu +1
Learning unsupervised representations of medical imaging cohorts can reveal anatomically meaningful prototypes without expert labels, which are often noisy and fail to capture true…
What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis
Xinghao Chen, Chak Tou Leong, Wenjin Guo +3
Latent Chain-of-Thought (CoT) internalizes reasoning within continuous hidden states, offering a promising alternative to verbose discrete reasoning traces. However, robust latent…
CoMAP: Co-Evolving World Models and Agent Policies for LLM Agents
Youwei Liu, Jian Wang, Hanlin Wang +1
Equipping language agents with world models enables them to anticipate environment dynamics and evaluate candidate actions before execution. However, existing textual world models…
Probing Cultural Awareness in LLMs: A Case Study of Cross-Culture Aesthetic Stylistics
Jiashuo Wang, Fenggang Yu, Jian Wang +6
Large Language Models (LLMs) are increasingly deployed in diverse cultural contexts, yet their ability to master aesthetic stylistics, i.e., the strategic use of language to evoke…
Seeing Isn't Believing: Mitigating Belief Inertia via Active Intervention in Embodied Agents
Hanlin Wang, Chak Tou Leong, Jian Wang +1
Recent advancements in large language models (LLMs) have enabled agents to tackle complex embodied tasks through environmental interaction. However, these agents still make subopti…
Foresight Optimization for Strategic Reasoning in Large Language Models
Jiashuo Wang, Jiawen Duan, Jian Wang +6
Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-based LLMs to perform effectiv…
Finding RELIEF: Shaping Reasoning Behavior without Reasoning Supervision via Belief Engineering
Chak Tou Leong, Dingwei Chen, Heming Xia +4
Large reasoning models (LRMs) have achieved remarkable success in complex problem-solving, yet they often suffer from computational redundancy or reasoning unfaithfulness. Current…
Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models
Youwei Liu, Jian Wang, Hanlin Wang +2
Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act without accessing real environments. Curr…
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…
E2CL: Exploration-based Error Correction Learning for Embodied Agents
Hanlin Wang, Chak Tou Leong, Jian Wang +1
Language models are exhibiting increasing capability in knowledge utilization and reasoning. However, when applied as agents in embodied environments, they often suffer from misali…
No Two Devils Alike: Unveiling Distinct Mechanisms of Fine-tuning Attacks
Chak Tou Leong, Yi Cheng, Kaishuai Xu +3
The existing safety alignment of Large Language Models (LLMs) is found fragile and could be easily attacked through different strategies, such as through fine-tuning on a few harmf…
Medical Dialogue Generation via Intuitive-then-Analytical Differential Diagnosis
Kaishuai Xu, Wenjun Hou, Yi Cheng +2
Medical dialogue systems have attracted growing research attention as they have the potential to provide rapid diagnoses, treatment plans, and health consultations. In medical dial…
COOPER: Coordinating Specialized Agents towards a Complex Dialogue Goal
Yi Cheng, Wenge Liu, Jian Wang +5
In recent years, there has been a growing interest in exploring dialogues with more complex goals, such as negotiation, persuasion, and emotional support, which go beyond tradition…
Self-Detoxifying Language Models via Toxification Reversal
Chak Tou Leong, Yi Cheng, Jiashuo Wang +2
Language model detoxification aims to minimize the risk of generating offensive or harmful content in pretrained language models (PLMs) for safer deployment. Existing methods can b…