2 citations · 3 across the 16 of their papers we have counts for
18 papers
OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong +33
Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of f…
AOHP: An Open-Source OS-Level Agent Harness for Personalized, Efficient and Secure Interaction
Shanhui Zhao, Jiacheng Liu, Guohong Liu +13
AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data s…
CLI-Anything: Towards Agent-Native Computer Use
Yuhao Yang, Tianyu Fan, Chao Huang
As large language models advance in reasoning and tool use capabilities, researchers increasingly seek to leverage them for computer use agents that can interact with existing soft…
When Does Hierarchy Help? Benchmarking Agent Coordination in Event-Driven Industrial Scheduling
Ziqi Wang, Yuhao Yang, Zhiwei Ling +2
Recent advances in agent and multi-agent systems have shown strong performance on tool use, reasoning, and collaborative tasks. However, existing benchmarks mostly evaluate task co…
Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence
NVIDIA, :, Amala Sanjay Deshmukh +204
We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 N…
GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, :, Aohan Zeng +184
We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…
S2SServiceBench: A Multimodal Benchmark for Last-Mile S2S Climate Services
Chenyue Li, Wen Deng, Zhuotao Sun +9
Subseasonal-to-seasonal (S2S) forecasts play an essential role in providing a decision-critical weeks-to-months planning window for climate resilience and sustainability, yet a gro…
See-Control: A Multimodal Agent Framework for Smartphone Interaction with a Robotic Arm
Haoyu Zhao, Weizhong Ding, Yuhao Yang +4
Recent advances in Multimodal Large Language Models (MLLMs) have enabled their use as intelligent agents for smartphone operation. However, existing methods depend on the Android D…
OmniFuser: Adaptive Multimodal Fusion for Service-Oriented Predictive Maintenance
Ziqi Wang, Hailiang Zhao, Yuhao Yang +7
Accurate and timely prediction of tool conditions is critical for intelligent manufacturing systems, where unplanned tool failures can lead to quality degradation and production do…
UltraCUA: A Foundation Model for Computer Use Agents with Hybrid Action
Yuhao Yang, Zhen Yang, Zi-Yi Dou +10
Computer-use agents face a fundamental limitation. They rely exclusively on primitive GUI actions (click, type, scroll), creating brittle execution chains prone to cascading failur…
Hi-Agent: Hierarchical Vision-Language Agents for Mobile Device Control
Zhe Wu, Hongjin Lu, Junliang Xing +10
Building agents that autonomously operate mobile devices has attracted increasing attention. While Vision-Language Models (VLMs) show promise, most existing approaches rely on dire…
Ferret-UI Lite: Lessons from Building Small On-Device GUI Agents
Zhen Yang, Zi-Yi Dou, Di Feng +13
Developing autonomous agents that effectively interact with Graphic User Interfaces (GUIs) remains a challenging open problem, especially for small on-device models. In this paper,…
Scaling Synthetic Task Generation for Agents via Exploration
Ram Ramrakhya, Andrew Szot, Omar Attia +6
Post-Training Multimodal Large Language Models (MLLMs) to build interactive agents holds promise across domains such as computer-use, web navigation, and robotics. A key challenge…
MTRDrive: Memory-Tool Synergistic Reasoning for Robust Autonomous Driving in Corner Cases
Ziang Luo, Kangan Qian, Jiahua Wang +13
Vision-Language Models(VLMs) have demonstrated significant potential for end-to-end autonomous driving, yet a substantial gap remains between their current capabilities and the rel…
Learning Intrinsic Water-Quality Dynamics with Rainfall for Data-Driven Forecasting
Ziqi Wang, Hailiang Zhao, Cheng Bao +5
Rainfall is an important environmental driver of water-quality variations through processes such as runoff, pollutant transport, dilution, and resuspension. Traditional mechanistic…
Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations
Yuhao Yang, Zhi Ji, Zhaopeng Li +8
Generative models have recently gained attention in recommendation systems by directly predicting item identifiers from user interaction sequences. However, existing methods suffer…
SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation
Jingxuan Chen, Derek Yuen, Bin Xie +14
Smartphone agents are increasingly important for helping users control devices efficiently, with (Multimodal) Large Language Model (MLLM)-based approaches emerging as key contender…
Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction
Haoran Luo, Haihong E, Yuhao Yang +10
Beyond traditional binary relational facts, n-ary relational knowledge graphs (NKGs) are comprised of n-ary relational facts containing more than two entities, which are closer to…