mlsanityData to 14 Oct 2026

WebRider: Persona-Conditioned Intent Controllers for Live-Web Assistance

arXiv 2608.06704 ↗First posted 7 Aug 2026cs.AI cs.HCcited by 0

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Abstract (arXiv)

Delegating a web task involves more than asking a question; it requires transferring a policy: what to verify, how to handle uncertainty, which preferences matter, and when to stop. Yet, current live-web agents are evaluated solely on the final answer, ignoring the policy constraints that define the delegation. A plausible final answer can conceal violations of that policy. Our full live audit reveals this critical gap: a strong controller completes 99.2% of tasks but honors all policy constraints in only 38.8% of cases. Finishing does not imply fidelity. WebRider bridges this gap by formalizing the delegated policy as an intent contract---an operational record of goals, constraints, evidence obligations, answer form, and task-local persona controls that must hold even as web pages change. WebRider employs a hierarchical architecture: a top-layer controller maintains the contract, a middle layer realizes intentions as guarded executable actions, and a tool layer executes these actions via browser, search, and maps tools. Our benchmark, RiderBench, evaluates this design on 4,096 live-web contracts across 42 public websites, auditing both the internal contract state and the visible user experience to determine if a rollout preserved its policy and if the steps were persona-consistent. The guarded middle interface also serves as a high-quality training signal; an 8B action-policy model trained through this interface outperforms executable-only baselines under a fixed controller. By making the browsing path a first-class object, WebRider enables a system that is auditable, human-judgeable, and learnable without conflating action realization with final-answer decisions. Dataset URL: hf.co/datasets/WebRider/WebRider.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 24 of its 31 references that are in the map. First posted on arXiv 7 Aug 2026.

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24 of 31 references.

References · 24

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
  3. 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,251
  4. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,242
  5. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,195
  6. 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 563
  7. 2024WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?cited by 363
  8. 2024WebLINX: Real-World Website Navigation with Multi-Turn Dialoguecited by 180
  9. 2024The BrowserGym Ecosystem for Web Agent Researchcited by 161
  10. 2023Multimodal Web Navigation with Instruction-Finetuned Foundation Modelscited by 160
  11. 2024ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agentscited by 133
  12. 2025AgentRewardBench: Evaluating Automatic Evaluations of Web Agent Trajectoriescited by 108
12 more
  1. 2025Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judgecited by 76
  2. 2024Large Language Models Empowered Personalized Web Agentscited by 66
  3. 2025RealWebAssist: A Benchmark for Long-Horizon Web Assistance with Real-World Userscited by 21
  4. 2025BrowserArena: Evaluating LLM Agents on Real-World Web Navigation Taskscited by 14
  5. 2026Persona2Web: Benchmarking Personalized Web Agents for Contextual Reasoning with User Historycited by 14
  6. 2026World-Model-Augmented Web Agents with Action Correctioncited by 9
  7. 2026Why Do LLM-based Web Agents Fail? A Hierarchical Planning Perspectivecited by 9
  8. 2026Emergence WebVoyager: Toward Consistent and Transparent Evaluation of (Web) Agents in The Wildcited by 5
  9. 2026Avenir-Web: Human-Experience-Imitating Multimodal Web Agents with Mixture of Grounding Expertscited by 4
  10. 2026Mobile GUI Agent Privacy Personalization with Trajectory Induced Preference Optimizationcited by 2
  11. 2026PersonaFingerprint: Measuring Persona Inference on Modern Websites with LLM-Driven Browsingcited by 2
  12. 2026SimPersona: Learning Discrete Buyer Personas from Raw Clickstreams for Grounded E-Commerce Agentscited by 1

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  1. 2026Before Acting, Change the State: Prospective State Intervention for Web Agents under Deceptive Interfaces
  2. 2026SovereignPA-Bench: Evaluating User-Owned Personal Agents under Evolving Intent, Platform Mediation, and Consent Constraints
  3. 2025WebGuard: Building a Generalizable Guardrail for Web Agents
  4. 2026MyPCBench: A Benchmark for Personally Intelligent Computer-Use Agents
  5. 2026Falsifiable Commitment Planning for Self-Correcting Web Agents
  6. 2026WebPageBench: Event-Level Verification and Controlled UI-Variant Generation for Web Agents
  7. 2026π-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows
  8. 2026Web Agents Should Use Typed Actions Instead of Click-Based Browsing