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Open-Weight MLLMs Cannot Compare What They Cannot Name

Paper recorded by Signals 4 on 2026-10-30 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-30 on arXiv · recorded by Signals 4 on 2026-11-02

Category: cs.CV · 计算机视觉 · first seen 2026-11-02

Abstract

Multimodal Large Language Models (MLLMs) are increasingly capable of understanding images and performing complex visual reasoning, suggesting the possibility of using them to automate biological image analysis. This need is becoming increasingly urgent as advances in technology continue to generate ever larger and more diverse microscopy datasets, already exceeding the scale at which manual visual

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#47 most recent of 710 cs.CV papers we have recorded · ↑ newer: Movens-Zero: Scaling Humanoid Motion Foundation Models with Large-Scal · ↓ older: ReuScope: Auditing Data Reuse and Evaluation Sensitivity in Capsule Vi
Cite this page: Open-Weight MLLMs Cannot Compare What They Cannot Name: the #47 most recent of 710 cs.CV papers we have recorded (as of 2026-10-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/open-weight-mllms-cannot-compare-what-they-cannot-name.html
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