Hao Cheng

Dyna-Mind: Learning to Simulate from Experience for Better AI Agents

Training Large Reasoning Models Efficiently via Progressive Thought Encoding

Dyna-Think: Synergizing Reasoning, Acting, and World Model Simulation in AI Agents

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

Coupling Attention and Memory: A Dynamic Memory Module for Efficient Adapation with Pretrained LLMs

CollabLLM: From Passive Responders to Active Collaborators

Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generation

SAS: Simulated Attention Score

ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning

Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass

SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents

LoRC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy

Model Tells Itself Where to Attend: Steerable Prompting for Reliable Reading Comprehension of LLM