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cs.CV2026

An Exam for Active Observers

Jiarui Zhang, Muzi Tao, Shangshang Wang +3

Human vision is a closed loop: gaze is continuously redirected by intermediate hypotheses rather than a single snapshot. Decades of psychophysics and cognitive science have argued…

cs.CV2026

AgroOmni: A Large-Scale Multi-view Agricultural Dataset for Cross-Scale Multimodal Reasoning

Jiarui Zhang, Junqi Hu, Zurong Mai +10

Modern agricultural data is sourced from diverse platforms and spans multiple spatial scales, ranging from ground-level close-up photography to Unmanned Aerial Vehicle (UAV) aerial…

cs.CV2026

AgroTools: A Benchmark for Tool-Augmented Multimodal Agents in Agriculture

Zi Ye, Yibin Wen, Xiaoya Fan +10

Agricultural decision-making increasingly requires multimodal systems that can transform visual observations into reliable, executable actions. However, existing agricultural multi…

cs.CV2026

MM-Zero: Self-Evolving Multi-Model Vision Language Models From Zero Data

Zongxia Li, Hongyang Du, Chengsong Huang +8

Self-evolving has emerged as a key paradigm for improving foundational models such as Large Language Models (LLMs) and Vision Language Models (VLMs) with minimal human intervention…

cs.CV2025

MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMs

Jiarui Zhang, Mahyar Khayatkhoei, Prateek Chhikara +1

Multimodal Large Language Models (MLLMs) have experienced rapid progress in visual recognition tasks in recent years. Given their potential integration into many critical applicati…

cs.CV2024

Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions

Jiarui Zhang, Ollie Liu, Tianyu Yu +2

Multimodal large language models (MLLMs) have made rapid progress in recent years, yet continue to struggle with low-level visual perception (LLVP) -- particularly the ability to a…