7 citations · 14 across the 8 of their papers we have counts for
8 papers
SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents via Distilled Structured Reasoning
Kaiwen Zhou, Ahmed Elgohary, A S M Iftekhar +1
The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for discovering vulnerabilities and ensuring…
Game-TARS: Pretrained Foundation Models for Scalable Generalist Multimodal Game Agents
Zihao Wang, Xujing Li, Yining Ye +24
We present Game-TARS, a generalist game agent trained with a unified, scalable action space anchored to human-aligned native keyboard-mouse inputs. Unlike API- or GUI-based approac…
UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Haoming Wang, Haoyang Zou, Huatong Song +109
The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have sh…
UI-TARS: Pioneering Automated GUI Interaction with Native Agents
Yujia Qin, Yining Ye, Junjie Fang +32
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., keyboard and mouse operations). U…
StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models
Zhicheng Guo, Sijie Cheng, Hao Wang +6
Large Language Models (LLMs) have witnessed remarkable advancements in recent years, prompting the exploration of tool learning, which integrates LLMs with external tools to addres…
RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generation
Qinyu Luo, Yining Ye, Shihao Liang +10
Generative models have demonstrated considerable potential in software engineering, particularly in tasks such as code generation and debugging. However, their utilization in the d…
Investigate-Consolidate-Exploit: A General Strategy for Inter-Task Agent Self-Evolution
Cheng Qian, Shihao Liang, Yujia Qin +6
This paper introduces Investigate-Consolidate-Exploit (ICE), a novel strategy for enhancing the adaptability and flexibility of AI agents through inter-task self-evolution. Unlike…
QASnowball: An Iterative Bootstrapping Framework for High-Quality Question-Answering Data Generation
Kunlun Zhu, Shihao Liang, Xu Han +4
Recent years have witnessed the success of question answering (QA), especially its potential to be a foundation paradigm for tackling diverse NLP tasks. However, obtaining sufficie…