activity
20242026
most citedGraph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

8 citations · 8 across the 10 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.CL2025

Well Begun, Half Done: Reinforcement Learning with Prefix Optimization for LLM Reasoning

Yiliu Sun, Zicheng Zhao, Yang Wei +2

Reinforcement Learning with Verifiable Rewards (RLVR) significantly enhances the reasoning capability of Large Language Models (LLMs). Current RLVR approaches typically conduct tra…

cs.AI2025

ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints

Rui Xu, Dakuan Lu, Zicheng Zhao +5

Spatial reasoning is a key capability in the field of artificial intelligence, especially crucial in areas such as robotics, computer vision, and natural language understanding. Ho…

cs.CL2025

Analysing Knowledge Construction in Online Learning: Adapting the Interaction Analysis Model for Unstructured Large-Scale Discourse

Jindi Wang, Yidi Zhang, Zhaoxing Li +4

The rapid expansion of online courses and social media has generated large volumes of unstructured learner-generated text. Understanding how learners construct knowledge in these s…

cs.AI2025

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…

cs.AI2025

CortexDebate: Debating Sparsely and Equally for Multi-Agent Debate

Yiliu Sun, Zicheng Zhao, Sheng Wan +1

Nowadays, single Large Language Model (LLM) struggles with critical issues such as hallucination and inadequate reasoning abilities. To mitigate these issues, Multi-Agent Debate (M…

cs.CL2025

Fast-Slow-Thinking: Complex Task Solving with Large Language Models

Yiliu Sun, Yanfang Zhang, Zicheng Zhao +3

Nowadays, Large Language Models (LLMs) have been gradually employed to solve complex tasks. To face the challenge, task decomposition has become an effective way, which proposes to…