WebNavigator: Global Web Navigation via Interaction Graph Retrieval
cs.IR, cs.AI
Submitted: 2026-03-20
Updated: 2026-10-03
Comments: Accepted at NeurIPS 2026. Updated version with additional experiments. 30 pages including references and appendices
License: http://creativecommons.org/licenses/by/4.0/
The gist: Despite significant advances in autonomous web navigation, current methods remain far from human-level performance in complex web environments.
Abstract
Despite significant advances in autonomous web navigation, current methods remain far from human-level performance in complex web environments. We argue that this limitation stems from Topological Blindness, where agents are forced to explore via trial-and-error without access to the global topological structure of the environment. To overcome this limitation, we introduce WebNavigator, which reframes web navigation from probabilistic exploration into deterministic retrieval and pathfinding. WebNavigator constructs Interaction Graphs via zero-token cost heuristic exploration offline and implements a Retrieve-Reason-Teleport workflow for global navigation online. WebNavigator achieves state-of-the-art performance on WebArena and OnlineMind2Web. On WebArena multi-site tasks, WebNavigator achieves a 72.9% success rate, more than doubling the performance of enterprise-level agents. This work reveals that Topological Blindness, rather than model reasoning capabilities alone, is an underestimated bottleneck in autonomous web navigation.
Sources
- Branch-and-Browse: Efficient and Controllable Web Exploration with Tree-Structured Reasoning and Action Memory
- SteP: Stacked LLM Policies for Web Actions
- An Illusion of Progress? Assessing the Current State of Web Agents
- Towards Enterprise-Ready Computer Using Generalist Agent
- WebATLAS: An LLM Agent with Experience-Driven Memory and Action Simulation
- Glyph: Scaling Context Windows via Visual-Text Compression
- DeepSeek-OCR: Contexts Optical Compression
- Training Verifiers to Solve Math Word Problems
- Autonomous Evaluation and Refinement of Digital Agents
- The BrowserGym Ecosystem for Web Agent Research
- Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems
- jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images
Related papers
- The Price of Isolation: Estimating the Ecosystem Cost of Symmetric Two-Sided A/B Testing
- SCAR: Semantic Continuity-Aware Retrieval for Efficient Context Expansion in RAG
- MixLoRA-DSI: Dynamically Expandable Mixture-of-LoRA Experts for Rehearsal-Free Generative Retrieval over Dynamic Corpora
- How Do LLM-Generated Texts Impact Term-Based Retrieval Models?
- MemSyco-Bench: Benchmarking Sycophancy in Agent Memory
- Training with Missed Targets in Generative Recommendation: Separating Supervision from Probability Competition