FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents

arXiv:2510.03204 · cs.CL · Submitted 2025-10-03 · Read on arXiv

cs.CL

Submitted: 2025-10-03

Updated: 2026-08-29

Code: https://github.com/ServiceNow/AgentLab

Terminology

Pruning — 66× in this paper · explained in 4 episodes
Benchmark — 25× in this paper · explained in 2 episodes
Ablation — 5× in this paper · explained in 1 episode
Success Rates — 5× in this paper
Clustering — 4× in this paper · explained in 2 episodes
Embeddings — 3× in this paper · explained in 2 episodes
Semantic Similarity — 3× in this paper · explained in 2 episodes
Ablation study — 2× in this paper · explained in 1 episode
Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
AI Agents — 1× in this paper · explained in 2 episodes
Attack Success Rate (ASR) — 1× in this paper · explained in 2 episodes
Attack Success Rates — 1× in this paper
Benchmarking — 1× in this paper · explained in 3 episodes
Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
Core — 1× in this paper · explained in 2 episodes
Document Object Model — 1× in this paper
Foundation Model — 1× in this paper · explained in 3 episodes
Foundation Models — 1× in this paper · explained in 7 episodes
Generalizability — 1× in this paper · explained in 6 episodes
Grounding — 1× in this paper · explained in 3 episodes
In-Context Learning — 1× in this paper · explained in 4 episodes
Prompt Engineering — 1× in this paper · explained in 4 episodes
Transformer — 1× in this paper · explained in 2 episodes
Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

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