2 citations · 3 across the 4 of their papers we have counts for
4 papers
H2Table: Hierarchical Hypergraph-Enhanced Large Language Models for Complex Table Reasoning
Jia Ling, Yangfan Wang, Chen Tang +4
Tables are ubiquitous across diverse domains, yet reasoning over them remains a significant challenge for modern large language models (LLMs). Current approaches typically lineariz…
MedCalc-R1: Knowledge-Guided Reward Framework for Medical Mathematical Reasoning
Haotian Wang, Lian Yan, Xingzhi Yao +4
In Reinforcement Learning with Verifiable Rewards (RLVR) frameworks for mathematical reasoning tasks, floating-point results are typically evaluated using a tolerance-based reward.…
AgriEval: A Comprehensive Chinese Agricultural Benchmark for Large Language Models
Lian Yan, Haotian Wang, Chen Tang +5
In the agricultural domain, the deployment of large language models (LLMs) is hindered by the lack of training data and evaluation benchmarks. To mitigate this issue, we propose Ag…
Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System
Haotian Wang, Xiyuan Du, Weijiang Yu +5
Multi-agent debate system (MAD) imitating the process of human discussion in pursuit of truth, aims to align the correct cognition of different agents for the optimal solution. It…