mlsanityData to 7 Oct 2026

VeriTrip: A Verifiable Benchmark for Travel Planning Agents over Unstructured Web Corpora

arXiv 2605.28683 ↗First posted 27 May 2026cs.AIcited by 0

On the map: LLM agents and tool use → Multimodal and embodied agents

Abstract (arXiv)

Existing benchmarks have laid the foundation for travel planning agents by establishing API-centric paradigms. However, as the capabilities of Autonomous Agents continue to advance, their evaluation must evolve beyond simple tool execution toward handling the inherent complexities of the open web. Current benchmarks bypass core cognitive hurdles: they fail to account for information noise, ignore multi-source factual contradictions, and overlook the necessity of grounding visual perception into logical planning. We introduce VeriTrip, a verifiable benchmark designed to meet the increasing demands for agent robustness and reliability. VeriTrip shifts the evaluation focus to evidence-grounded reasoning over unstructured multimodal web corpora. It establishes a Multimodal Retrieval Base (MRB) derived from real-world sources, forcing agents to autonomously orchestrate queries across heterogeneous data. A synchronized Verifiable Knowledge Base (VKB) enables a cell-wise verification protocol that precisely quantifies factual reliability, distinguishing systematic reasoning failures from parametric hallucinations. Our evaluations across leading MLLMs reveal a critical textitretrieval-reasoning trade-off: the cognitive load of autonomous retrieval significantly erodes instruction retention. VeriTrip provides the rigorous foundation necessary for the next generation of planning agents capable of operating in unconstrained, multimodal environments.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 19 of its 26 references that are in the map. First posted on arXiv 27 May 2026.

Builds on

19 of 26 references.

References · 19

  1. 2025Qwen3 Technical Reportcited by 8,195
  2. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
  3. 2024GPT-4o System Cardcited by 4,467
  4. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,655
  5. 2025Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Modelscited by 1,175
  6. 2023GAIA: a benchmark for General AI Assistantscited by 1,084
  7. 2025BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agentscited by 616
  8. 2024TravelPlanner: A Benchmark for Real-World Planning with Language Agentscited by 385
  9. 2025DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agentscited by 236
  10. 2025BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agentcited by 183
  11. 2024A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learningcited by 74
  12. 2025Deep Research: A Survey of Autonomous Research Agentscited by 63
7 more
  1. 2025DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Researchcited by 51
  2. 2025DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Searchcited by 41
  3. 2024TravelAgent: An AI Assistant for Personalized Travel Planningcited by 38
  4. 2025DeepScholar-Bench: A Live Benchmark and Automated Evaluation for Generative Research Synthesiscited by 31
  5. 2025Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modalitycited by 30
  6. 2025TripTailor: A Real-World Benchmark for Personalized Travel Planningcited by 22
  7. 2024RAP: Retrieval-Augmented Planner for Adaptive Procedure Planning in Instructional Videoscited by 6

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2025TP-RAG: Benchmarking Retrieval-Augmented Large Language Model Agents for Spatiotemporal-Aware Travel Planning
  2. 2025VeriWeb: Verifiable Long-Chain Web Benchmark for Agentic Information-Seeking
  3. 2025City Navigation in the Wild: Exploring Emergent Navigation from Web-Scale Knowledge in MLLMs
  4. 2026Revisiting the Travel Planning Capabilities of Large Language Models
  5. 2026MapTab: A Diagnostic Benchmark for Long-Horizon Multi-Criteria Multimodal Reasoning on Heterogeneous Topological Graphs
  6. 2026TREK: A Travel Reasoning and Evaluation Kit for LLM Agents in Complex Trip Planning
  7. 2024A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models
  8. 2025WebCoT: Enhancing Web Agent Reasoning by Reconstructing Chain-of-Thought in Reflection, Branching, and Rollback