43 citations · 129 across the 62 of their papers we have counts for
8 papers · 2 filters
WebHarbor: Docking Real Websites for Evolving GUI Agent Environments
Zhaoyang Wang, Qianhui Wu, Boyu Gou +54
GUI web agents require realistic and interactive environments that remain stable during both evaluation and training. Live website evaluation suffers from changing content, access…
ParetoSaddler: Pareto-Guided Optimization of Agent Harnesses for Quality and Cost
Xingzhi Qian, Sungho Park, Rongyuan Tan +13
Harness optimization can substantially improve LLM agents without modifying model weights, but existing methods primarily optimize response quality. Extending them to joint quality…
Agentic World Modeling for Agent Test-time Scaling without Environment Replica
Wendi Li, Huseyin A. Inan, Wei-Ning Chen +4
Test-time scaling (TTS) improves large language model agents by sampling and selecting among multiple candidate trajectories, but common realizations assume that these trajectories…
FOCUS: Training-Free Decision-Preserving Context Compression for LLM Agents
Shantanu Dixit, Anson Bastos, Xuchao Zhang +2
LLM agents accumulate interaction histories that grow linearly with task length, causing quadratic inference cost scaling and performance degradation from attention dilution. Exist…
ActionNex: A Virtual Outage Manager for Cloud Computing
Zhenfeng Lin, Haoji Hu, Ming Hao +11
Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven decisions under partial observabili…
WebXSkill: Skill Learning for Autonomous Web Agents
Zhaoyang Wang, Qianhui Wu, Xuchao Zhang +12
Autonomous web agents powered by large language models (LLMs) remain brittle on long-horizon browser workflows. A key bottleneck is a grounding gap in existing skill formulations:…
Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity
Menglin Xia, Xuchao Zhang, Shantanu Dixit +6
Agent memory systems must accommodate continuously growing information while supporting efficient, context-aware retrieval for downstream tasks. Abstraction is essential for scalin…
AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
Shraddha Barke, Arnav Goyal, Alind Khare +3
AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy tool outputs. We address this gap…