MELLON - Multimodal Enhanced LLM for Online Navigation
Web navigation agents are capable of addressing various types of tasks on different websites. Current baselines on web navigation are either unimodal or lack strong reasoning abilities given multimodal inputs. Focusing on the WebShop benchmark, a real-world website simulation, we explore the alignment of text and images, as well as multimodal reasoning and planning abilities, to enhance the performance of web navigation agents. We propose three innovative multimodal enhancements: Multimodal Enha
Record details
Published: 10 August 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Agents & autonomy
Retrieved: 11 August 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Multi-Agent AI Safety as an Institutional Design Problem
arXiv · 10 August 2026
Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy
arXiv · 10 August 2026
Agent Safety Should Be a Runtime Contract
HuggingFace Daily Papers · 10 August 2026
Toward a Theory of Value in AI Alignment
arXiv · 10 August 2026
Yesterday's Shield, Today's Spear: A Self-Evolving Safety Guardrail in Production
arXiv red teaming query · 9 August 2026
REDAgentBench: Executable Red Teaming and Faithful Measurement of LLM Agent Systems
arXiv red teaming query · 11 August 2026
How to cite this record
ethics.ai (10 August 2026), “MELLON - Multimodal Enhanced LLM for Online Navigation,” evidence record 18029, https://ethics.ai/record/18029 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.