# DETOUR: An Interactive Benchmark for Dual-Agent Search and Reasoning

arXiv: https://arxiv.org/abs/2602.00352 · HTML: https://mlsanity.com/paper/2602.00352/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 61 references that are in the map.
- First posted on arXiv 30 Jan 2026.

## Builds on (most cited first, 16 of 16)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
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- [A Survey on In-context Learning](https://mlsanity.com/paper/2301.00234/) (2022)
- [Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://mlsanity.com/paper/2406.11695/) (2024)
- [DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents](https://mlsanity.com/paper/2506.11763/) (2025)
- [DeepShop: A Benchmark for Deep Research Shopping Agents](https://mlsanity.com/paper/2506.02839/) (2025)
- [MedBrowseComp: Benchmarking Medical Deep Research and Computer Use](https://mlsanity.com/paper/2505.14963/) (2025)
- [MIMICS: A Large-Scale Data Collection for Search Clarification](https://mlsanity.com/paper/2006.10174/) (2020)
- [DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs](https://mlsanity.com/paper/2506.08500/) (2025)
- [Analyzing and Learning from User Interactions for Search Clarification](https://mlsanity.com/paper/2006.00166/) (2020)
- [User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation](https://mlsanity.com/paper/2501.04410/) (2025)
- [Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification](https://mlsanity.com/paper/2101.07124/) (2021)
- [Clarifying Ambiguities: on the Role of Ambiguity Types in Prompting Methods for Clarification Generation](https://mlsanity.com/paper/2504.12113/) (2025)
- [Browsing Lost Unformed Recollections: A Benchmark for Tip-of-the-Tongue Search and Reasoning](https://mlsanity.com/paper/2503.19193/) (2025)
- [ScIRGen: Synthesize Realistic and Large-Scale RAG Dataset for Scientific Research](https://mlsanity.com/paper/2506.11117/) (2025)
- [Tip of the Tongue Query Elicitation for Simulated Evaluation](https://mlsanity.com/paper/2502.17776/) (2025)

## Abstract (arXiv)

When recalling information in conversation, people often arrive at the recollection after multiple turns. However, existing benchmarks for evaluating agent capabilities in such tip-of-the-tongue search processes are restricted to single-turn settings. To more realistically simulate tip-of-the-tongue search, we introduce Dual-agent based Evaluation Through Obscure Under-specified Retrieval (DETOUR), a dual-agent evaluation benchmark containing 1,011 prompts. The benchmark design involves a Primary Agent, which is the subject of evaluation, tasked with identifying the recollected entity through querying a Memory Agent that is held consistent across evaluations. Our results indicate that current state-of-the-art models still struggle with our benchmark, only achieving 36% accuracy when evaluated on all modalities (text, image, audio, and video), highlighting the importance of enhancing capabilities in underspecified scenarios.