4 papers
EASy: Towards Efficient LLM-Based Agentic System
Junnan Liu, Linhao Luo, Thuy-Trang Vu +1
Agentic systems have emerged as a promising paradigm for solving complex tasks by coordinating specialized LLM-based agents. However, most existing systems primarily optimize task…
AIPO: Learning to Reason from Active Interaction
Junnan Liu, Linhao Luo, Thuy-Trang Vu +1
Recent advances in large language models (LLMs) have demonstrated remarkable reasoning capabilities, largely stimulated by Reinforcement Learning with Verifiable Rewards (RLVR). Ho…
G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge
Linhao Luo, Zicheng Zhao, Junnan Liu +9
Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented generation (RAG) mitigates this by inc…
SituatedThinker: Grounding LLM Reasoning with Real-World through Situated Thinking
Junnan Liu, Linhao Luo, Thuy-Trang Vu +1
Recent advances in large language models (LLMs) demonstrate their impressive reasoning capabilities. However, the reasoning confined to internal parametric space limits LLMs' acces…