OBLIQ-Bench: Exposing Overlooked Bottlenecks in Modern Retrievers with Latent and Implicit Queries
Retrieval benchmarks are increasingly saturating, but we argue that efficient search is far from a solved problem. We identify a class of queries we call oblique, which seek documents that instantiate a latent pattern, like finding all tweets that express an implicit stance, chat logs that demonstrate a particular failure mode, or transcripts that match an abstract scenario. We study three mechanisms through which obliqueness may arise and introduce OBLIQ-Bench, a suite of five oblique search problems over real long-tail corpora. OBLIQ-Bench exposes an overlooked asymmetry between retrieval and verification, where reasoning LLMs reliably recognize latent relevance whenever relevant docume...
| Authors | Diane Tchuindjo, Devavrat Shah, Omar Khattab |
|---|---|
| Primary category | cs.IR |
| Published | 7 May 2026 |
| Last updated at source | 28 May 2026 |
Models and datasets referencing this paper
- dianetc/OBLIQ-BenchDataset
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