👥 Multi-Agent

📷 CVPR2026 · 2 paper notes

📌 Same area in other venues: 🔬 ICLR2026 (47) · 💬 ACL2026 (40) · 🧪 ICML2026 (24) · 🤖 AAAI2026 (26) · 🧠 NeurIPS2025 (17) · 🧪 ICML2025 (7)

🔥 Top topics: Agents ×2

AgentDet: A Shared-Blackboard Multi-Agent Framework for Zero-/Few-Shot Object Detection

AgentDet decomposes zero-/few-shot object detection into four LLM agents: Scout, Pinner, Curator, and Judge. These agents collaborate via a "Shared Blackboard" and a patch-level "Knowledge Base" (KB). The framework fragments visual evidence into the KB, assembles them into holistic textual clues for LLM-based box prediction, and trains only the Judge agent. It achieves competitive results on PASCAL VOC and COCO for both ZSOD and FSOD tasks.

Visual Document Understanding and Reasoning: A Multi-Agent Collaboration Framework with Agent-Wise Adaptive Test-Time Scaling

MACT decomposes the "monolithic single-model" visual document QA into four agents with distinct roles: planning, execution, judging, and answering. It adaptively allocates test-time compute according to the cognitive load of each agent rather than uniformly increasing parameters. On 15 benchmarks, it consistently ranks in the top three with <30B parameters, achieving an average improvement of 9.9–11.5% over the base models.