11 papers
Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning
Junhong Lin, Shicheng Liu, Jinyeop Song +3
Knowledge-graph retrieval-augmented generation (KG-RAG) couples large language models (LLMs) with structured, verifiable knowledge graphs (KGs) to reduce hallucination and provide…
Interactive Inverse Reinforcement Learning of Interaction Scenarios via Bi-level Optimization
Yue Mao, Shicheng Liu, Siyuan Xu +1
Inverse reinforcement learning (IRL) learns a reward function and a corresponding policy that best fit the demonstration data of an expert. However, in the current IRL setting, the…
DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling
Shicheng Liu, Yucheng Jiang, Sajid Farook +3
Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysis. However, existing approaches…
Steering to Say No: Configurable Refusal via Activation Steering in Vision Language Models
Jiaxi Yang, Shicheng Liu, Yuchen Yang +1
With the rapid advancement of Vision Language Models (VLMs), refusal mechanisms have become a critical component for ensuring responsible and safe model behavior. However, existing…
Explainable reinforcement learning from human feedback to improve alignment
Shicheng Liu, Siyuan Xu, Wenjie Qiu +2
A common and effective strategy for humans to improve an unsatisfactory outcome in daily life is to find a cause of this outcome and correct the cause. In this paper, we investigat…
The Path of Self-Evolving Large Language Models: Achieving Data-Efficient Learning via Intrinsic Feedback
Hangfan Zhang, Siyuan Xu, Zhimeng Guo +8
Reinforcement learning (RL) has demonstrated potential in enhancing the reasoning capabilities of large language models (LLMs), but such training typically demands substantial effo…