arXiv AI
AutoTailor: Automatic, User-Aligned Capability Selection and Adaptation for Web Agents
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arXiv AI
Oct 12
Web$hell: A Unified Interface for Agentic Web Access
Web$hell is a unified interface that consolidates various web access methods—search, browser actions, and filesystem interactions—into a single model for large language model agents. It uses a WebContract schema to compile live webpages into addressable information and action objects, which are stored in a WebCache and manipulated through shared operations. Experiments across search, navigation, and research tasks show that Web$hell delivers strong performance at lower cost, highlighting the role of interface design in enhancing agentic web access.
arXiv Machine Learning
Sep 2
TRIAGE: Three-level Routing and Intelligent Agent Guidance for Efficient Execution
TRIAGE introduces a three-level routing framework for Large Language Model agents that reduces token consumption by reusing historical execution trajectories. The system classifies queries into direct reuse, skill substitution, and full ReAct levels, achieving significant token savings in large-scale security monitoring and cross-domain benchmarks. An automatic skill extraction mechanism further refines reusable patterns, creating a positive feedback loop that improves efficiency over time.
arXiv Machine Learning
Aug 18
When Tool-Backed Skill Retrieval Fails: Source-Style Collapse in Executable Capability Retrieval
arXiv:2608. 16502v1 Announce Type: new Abstract: Large-scale agents increasingly rely on retrieval to access external capabilities.
arXiv AI
Jun 18
WebSP-Eval: Evaluating Web Agents on Website Security and Privacy Tasks
arXiv:2604. 06367v2 Announce Type: replace-cross Abstract: Web agents automate browser tasks, ranging from simple form completion to complex workflows like ordering groceries.
arXiv AI
Oct 15
HyWe: Unifying Search and Operation for Real-World Hybrid Web Tasks
arXiv:2610.16319v1 Announce Type: new Abstract: Real-world hybrid web tasks need both information gathering and page interaction, yet search-based and operation-based agents are developed and evaluat...
arXiv AI
Aug 11
WebChoreArena: Evaluating Web Browsing Agents on Realistic Tedious Web Tasks
arXiv:2506. 01952v2 Announce Type: replace-cross Abstract: Powered by large language models (LLMs), web browsing agents operate graphical user interfaces in a human-like manner, offering a transparent and general framework for automating web-based tasks.