activity
20242026
most citedInfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning

2 citations · 2 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2026

WisdomInterrogatory (LuWen): An Open-Source Legal Large Language Model Technical Report

Yiquan Wu, Yuhang Liu, Yifei Liu +4

Large language models have demonstrated remarkable capabilities across a wide range of natural language processing tasks, yet their application in the legal domain remains challeng…

cs.CL2025

Graph2Eval: Automatic Multimodal Task Generation for Agents via Knowledge Graphs

Yurun Chen, Xavier Hu, Yuhan Liu +8

As multimodal LLM-driven agents advance in autonomy and generalization, traditional static datasets face inherent scalability limitations and are insufficient for fully assessing t…

cs.CL2025

HarmonyGuard: Toward Safety and Utility in Web Agents via Adaptive Policy Enhancement and Dual-Objective Optimization

Yurun Chen, Xavier Hu, Yuhan Liu +4

Large language models enable agents to autonomously perform tasks in open web environments. However, as hidden threats within the web evolve, web agents face the challenge of balan…

cs.AI2025

InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization

Yuhang Liu, Zeyu Liu, Shuanghe Zhu +10

The emergence of Multimodal Large Language Models (MLLMs) has propelled the development of autonomous agents that operate on Graphical User Interfaces (GUIs) using pure visual inpu…

cs.AI2025

Infi-MMR: Curriculum-based Unlocking Multimodal Reasoning via Phased Reinforcement Learning in Multimodal Small Language Models

Zeyu Liu, Yuhang Liu, Guanghao Zhu +9

Recent advancements in large language models (LLMs) have demonstrated substantial progress in reasoning capabilities, such as DeepSeek-R1, which leverages rule-based reinforcement…

cs.AI2025

InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners

Yuhang Liu, Pengxiang Li, Congkai Xie +5

Multimodal Large Language Models (MLLMs) have powered Graphical User Interface (GUI) Agents, showing promise in automating tasks on computing devices. Recent works have begun explo…