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Study questions if biological reasoning models truly use biological inputs

A new research paper investigates whether biological reasoning models effectively utilize their biological inputs. The study tested six models across DNA, protein, and single-cell tasks by perturbing biological inputs and analyzing model outputs. Findings indicate that some models, like Evo2 and ESM3, contribute minimally to performance, with models often relying more on text than provided biological data. However, other models such as ChatNT, Prot2Text-V2, and CellWhisperer showed that foundation model inputs do contribute to their performance. AI

IMPACT Raises questions about the effectiveness of current training strategies for biological reasoning models.

RANK_REASON Research paper analyzing model behavior and input utilization. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Study questions if biological reasoning models truly use biological inputs

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Research paper analyzing model behavior and input utilization. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ada Fang, Nikitha Thoduguli, Lukas Fesser, Hanlin Zhang, Sham M. Kakade, Marinka Zitnik ·

    When Do Biological Reasoning Models Use Their Biological Inputs?

    arXiv:2610.00898v1 Announce Type: new Abstract: Biological reasoning models use post-training to connect LLMs to biological foundation model representations and biological text. Their benchmark accuracy is taken as evidence that LLMs reason over these inputs. We test this assumpt…