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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…