4 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents
Imene Kerboua, Sahar Omidi Shayegan, Megh Thakkar +7
Web agents powered by large language models (LLMs) must process lengthy web page observations to complete user goals; these pages often exceed tens of thousands of tokens. This sat…
How to Train Your LLM Web Agent: A Statistical Diagnosis
Dheeraj Vattikonda, Santhoshi Ravichandran, Emiliano Penaloza +13
LLM-based web agents have recently made significant progress, but much of it has occurred in closed-source systems, widening the gap with open-source alternatives. Progress has bee…
LineRetriever: Planning-Aware Observation Reduction for Web Agents
Imene Kerboua, Sahar Omidi Shayegan, Megh Thakkar +6
While large language models have demonstrated impressive capabilities in web navigation tasks, the extensive context of web pages, often represented as DOM or Accessibility Tree (A…