mlsanityData to 7 Oct 2026

Signal-Driven Observation for Long-Horizon Web Agents

arXiv 2606.06708 ↗First posted 4 Jun 2026cs.CLcited by 0

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

Web agents operating over long horizons ingest raw DOM and accessibility trees -- routinely tens of thousands of tokens -- at every action step, causing progressive context degradation that erodes reasoning well before tasks complete. We argue that this coupling of observation frequency to action frequency is an architectural mistake. Drawing on the insight from Recursive Language Models that querying a document outperforms reading it wholesale, we propose Signal-Driven Observation (SDO): a dedicated sub-call reads the full DOM but returns only task-relevant elements and their selectors, and is re-invoked only when a lightweight signal detector fires -- triggered by URL transitions, newly visible interactive elements, action failures, or exogenous browser events. We outline the open problems SDO introduces and call on the community to treat observation compression as a core architectural decision in web agent design.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 37 of its 39 references that are in the map. First posted on arXiv 4 Jun 2026.

Builds on

37 of 39 references.

Closest ancestors · 14

Same direction, newest first

  1. 2026Odysseys: Benchmarking Web Agents on Realistic Long Horizon Tasks27 Apr
  2. 2026Read More, Think More: Revisiting Observation Reduction for Web Agents2 Apr
  3. 2026StressWeb: A Diagnostic Benchmark for Web Agent Robustness under Realistic Interaction Variability27 Mar
  4. 2026Enhancing Web Agents with a Hierarchical Memory Tree7 Mar
  5. 2026M2: Dual-Memory Augmentation for Long-Horizon Web Agents via Trajectory Summarization and Insight Retrieval28 Feb
  6. 2025Lost in the Maze: Overcoming Context Limitations in Long-Horizon Agentic Search21 Oct
  7. 2025WAREX: Web Agent Reliability Evaluation on Existing Benchmarks28 Sep
  8. 2025LineRetriever: Planning-Aware Observation Reduction for Web Agents30 Jun
  9. 2025REAL: Benchmarking Autonomous Agents on Deterministic Simulations of Real Websites15 Apr
  10. 2025An Illusion of Progress? Assessing the Current State of Web Agents2 Apr
  11. 2024The BrowserGym Ecosystem for Web Agent Research6 Dec
  12. 2024WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?12 Mar
2 more
  1. 2023LASER: LLM Agent with State-Space Exploration for Web Navigation15 Sep
  2. 2023WebArena: A Realistic Web Environment for Building Autonomous Agents25 Jul

Other references · 23

  1. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,134
  2. 2023Language Models can Solve Computer Taskscited by 371
  3. 2024AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agentscited by 359
  4. 2025RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learningcited by 357
  5. 2024ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agentscited by 126
  6. 2025ACON: Optimizing Context Compression for Long-horizon LLM Agentscited by 126
  7. 2024Attacking Vision-Language Computer Agents via Pop-upscited by 112
  8. 2025AgenTracer: Who Is Inducing Failure in the LLM Agentic Systems?cited by 105
  9. 2025AgentFold: Long-Horizon Web Agents with Proactive Context Managementcited by 95
  10. 2025Recursive Language Modelscited by 94
  11. 2024WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Taskscited by 81
  12. 2024OfficeBench: Benchmarking Language Agents across Multiple Applications for Office Automationcited by 66
11 more
  1. 2025AgentRxiv: Towards Collaborative Autonomous Researchcited by 64
  2. 2025DoomArena: A framework for Testing AI Agents Against Evolving Security Threatscited by 31
  3. 2026Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agentscited by 28
  4. 2026The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Breakcited by 25
  5. 2025FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agentscited by 16
  6. 2025Evaluating Long-Context Reasoning in LLM-Based WebAgentscited by 15
  7. 2026ContextBudget: Budget-Aware Context Management for Long-Horizon Search Agentscited by 13
  8. 2026A Subgoal-driven Framework for Improving Long-Horizon LLM Agentscited by 10
  9. 2024Preemptive Detection and Correction of Misaligned Actions in LLM Agentscited by 9
  10. 2026Inherited Goal Drift: Contextual Pressure Can Undermine Agentic Goalscited by 6
  11. 2026BEAP-Agent: Backtrackable Execution and Adaptive Planning for GUI Agentscited by 1

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  1. 2026Region4Web: Rethinking Observation Space Granularity for Web Agents
  2. 2026WebChallenger: A Reliable and Efficient Generalist Web Agent
  3. 2026Revisiting Observation Reduction for Web Agents: Comprehensive Evaluation with a Lightweight Framework
  4. 2026Web Agents Should Use Typed Actions Instead of Click-Based Browsing
  5. 2025WebArxiv: A Reproducible Benchmark for Evaluating Multimodal Web Agents on arXiv Tasks
  6. 2026Monitoring Web Agents Without Internal Signals: Observable Trajectories and Key-Step Supervision
  7. 2026LongSeeker: Elastic Context Orchestration for Long-Horizon Search Agents
  8. 2026Out of Sight: Compression-Aware Content Protection against Agentic Crawlers