Benchmark for Assessing Olfactory Perception of Large Language Models
Here we introduce the Olfactory Perception (OP) benchmark, designed to assess the capability of large language models (LLMs) to reason about smell. The benchmark contains 1,010 questions across eight task categories spanning odor classification, odor primary descriptor identification, intensity and pleasantness judgments, multi-descriptor prediction, mixture similarity, olfactory receptor activation, and smell identification from real-world odor sources. Each question is presented in two prompt formats, compound names and isomeric SMILES, to evaluate the effect of molecular representations. Evaluating 21 model configurations across major model families, we find that compound-name prompts ...
| Authors | Eftychia Makri, Nikolaos Nakis, Laura Sisson et al. |
|---|---|
| Primary category | cs.CL |
| Published | 8 March 2026 |
| Last updated at source | 8 March 2026 |
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