Signals 4 · free daily AI digest

NeuronEye: Query-Guided Visual Concept Activation for Vision-Language Reasoning

Paper recorded by Signals 4 on 2026-09-29 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-29 on arXiv · recorded by Signals 4 on 2026-09-30

Category: cs.AI · 人工智能 · first seen 2026-09-30

Abstract

Current vision-language models (VLMs) encode visual information in dense hidden states where object identity, spatial layout, and local attributes are implicitly entangled rather than explicitly disentangled, limiting their ability to isolate and modulate the specific visual evidence required by a given language query. Inspired by sparse population coding and top-down modulation in biological visi

Read on arXiv →

#13 most recent of 460 cs.AI papers we have recorded · ↑ newer: Correct Answers, Invalid Traces: What Verifiable Grade-School Math Rev · ↓ older: Character Training for Risk-Averse Agents
Cite this page: NeuronEye: Query-Guided Visual Concept Activation for Vision-Language Reasoning: the #13 most recent of 460 cs.AI papers we have recorded (as of 2026-09-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/neuroneye-query-guided-visual-concept-activation-for-vision-language-reasoning.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions