most citedLarge Action Models: From Inception to Implementation

2 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

cs.SE2025

SWE-bench Goes Live!

Linghao Zhang, Shilin He, Chaoyun Zhang +12

The issue-resolving task, where a model generates patches to fix real-world bugs, has emerged as a critical benchmark for evaluating the capabilities of large language models (LLMs…

cs.AI2025

UFO2: The Desktop AgentOS

Chaoyun Zhang, He Huang, Chiming Ni +18

Recent Computer-Using Agents (CUAs), powered by multimodal large language models (LLMs), offer a promising direction for automating complex desktop workflows through natural langua…

cs.AI2025

API Agents vs. GUI Agents: Divergence and Convergence

Chaoyun Zhang, Shilin He, Liqun Li +5

Large language models (LLMs) have evolved beyond simple text generation to power software agents that directly translate natural language commands into tangible actions. While API-…

cs.CL2025

DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale

Linghao Zhang, Junhao Wang, Shilin He +13

Large Language Models have advanced automated software development, however, it remains a challenge to correctly infer dependencies, namely, identifying the internal components and…

cs.AI20252 cited

Large Action Models: From Inception to Implementation

Lu Wang, Fangkai Yang, Chaoyun Zhang +15

As AI continues to advance, there is a growing demand for systems that go beyond language-based assistance and move toward intelligent agents capable of performing real-world actio…

cs.AI2024

Large Language Model-Brained GUI Agents: A Survey

Chaoyun Zhang, Shilin He, Jiaxu Qian +10

GUIs have long been central to human-computer interaction, providing an intuitive and visually-driven way to access and interact with digital systems. The advent of LLMs, particula…