12 citations · 30 across the 17 of their papers we have counts for
4 papers · 2 filters
DeliveryBench: Can Agents Earn Profit in Real World?
Lingjun Mao, Jiawei Ren, Kun Zhou +3
LLMs and VLMs are increasingly deployed as embodied agents, yet existing benchmarks largely revolve around simple short-term tasks and struggle to capture rich realistic constraint…
OpenCUA: Open Foundations for Computer-Use Agents
Xinyuan Wang, Bowen Wang, Dunjie Lu +39
Vision-language models have demonstrated impressive capabilities as computer-use agents (CUAs) capable of automating diverse computer tasks. As their commercial potential grows, cr…
OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems
Xiaozhe Li, Jixuan Chen, Xinyu Fang +4
Large Language Models (LLMs) have shown remarkable capabilities in solving diverse tasks. However, their proficiency in iteratively optimizing complex solutions through learning fr…
Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis
Tianbao Xie, Jiaqi Deng, Xiaochuan Li +12
Graphical user interface (GUI) grounding, the ability to map natural language instructions to specific actions on graphical user interfaces, remains a critical bottleneck in comput…