5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.AI2026
GRAIN: Bridging Name and Narrative Shifts in Real-World Graph Reasoning through Invariance-Rewarded Agentic RL
Zike Yuan, Han Zhang, Jianzhi Yan +10
Despite their potential in standardized graph tasks, Large Language Models (LLMs) remain brittle to real-world shifts in node identifiers and task formulation. While deterministic…
cs.CL2025★ 5 cited
Baichuan-M1: Pushing the Medical Capability of Large Language Models
Bingning Wang, Haizhou Zhao, Huozhi Zhou +39
The current generation of large language models (LLMs) is typically designed for broad, general-purpose applications, while domain-specific LLMs, especially in vertical fields like…
cs.LG2018
: Active Learning over Hypergraphs
I Chien, Huozhi Zhou, Pan Li
We propose a hypergraph-based active learning scheme which we term , generalizes the previously reported algorithm originally proposed for graph-based active lea…