activity
20192026
most citedSolving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach

17 citations · 55 across the 28 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

cs.CL2025

G-KV: Decoding-Time KV Cache Eviction with Global Attention

Mengqi Liao, Lu Wang, Chaoyun Zhang +7

Recent reasoning large language models (LLMs) excel in complex tasks but encounter significant computational and memory challenges due to long sequence lengths. KV cache compressio…

cs.AI2025

GUI-360: A Comprehensive Dataset and Benchmark for Computer-Using Agents

Jian Mu, Chaoyun Zhang, Chiming Ni +14

We introduce GUI-360, a large-scale, comprehensive dataset and benchmark suite designed to advance computer-using agents (CUAs). CUAs present unique challenges and is const…

cs.DC2025

UFO3: Weaving the Digital Agent Galaxy

Chaoyun Zhang, Liqun Li, He Huang +8

Large language model (LLM)-powered agents are transforming digital devices from passive tools into proactive intelligent collaborators. However, most existing frameworks remain con…

cs.SE2025

From Task to Tutorial: An Automated GUI Framework for Excel Tutorial Document and Video Creation

Yuhang Xie, Jian Mu, Xiaojun Ma +9

Excel is one of the most widely used productivity tools across domains, offering rich functionality but also overwhelming users with its complexity. This creates a persistent deman…

cs.CL2025

GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents

Qianhui Wu, Kanzhi Cheng, Rui Yang +15

One of the principal challenges in building VLM-powered GUI agents is visual grounding, i.e., localizing the appropriate screen region for action execution based on both the visual…

cs.CL2025

Text2Grad: Reinforcement Learning from Natural Language Feedback

Hanyang Wang, Lu Wang, Chaoyun Zhang +5

Traditional RLHF optimizes language models with coarse, scalar rewards that mask the fine-grained reasons behind success or failure, leading to slow and opaque learning. Recent wor…

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★ 1 cited

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.AI2025★ 2 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…