most citedMemory in the Age of AI Agents

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Evo-MedAgent: Beyond One-Shot Diagnosis with Agents That Remember, Reflect, and Improve

Weixiang Shen, Bailiang Jian, Jun Li +6

Tool-augmented large language model (LLM) agents can orchestrate specialist classifiers, segmentation models, and visual question-answering modules to interpret chest X-rays. Howev…

cs.AI2026

PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory

Zhifei Xie, Zongzheng Hu, Fangda Ye +10

Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive agent: depth, complexity, ambigui…

cs.AI2026

TheraAgent: Multi-Agent Framework with Self-Evolving Memory and Evidence-Calibrated Reasoning for PET Theranostics

Zhihao Chen, Jiahui Wang, Yizhou Chen +8

PET theranostics is transforming precision oncology, yet treatment response varies substantially; many patients receiving 177Lu-PSMA radioligand therapy (RLT) for metastatic castra…

cs.CL20261 cited

Memory in the Age of AI Agents

Yuyang Hu, Shichun Liu, Yanwei Yue +44

Memory has emerged, and will continue to remain, a core capability of foundation model-based agents. As research on agent memory rapidly expands and attracts unprecedented attentio…

cs.CV2025

VisMem: Latent Vision Memory Unlocks Potential of Vision-Language Models

Xinlei Yu, Chengming Xu, Guibin Zhang +7

Despite the remarkable success of Vision-Language Models (VLMs), their performance on a range of complex visual tasks is often hindered by a "visual processing bottleneck": a prope…

cs.MA2025

MAS: Self-Generative, Self-Configuring, Self-Rectifying Multi-Agent Systems

Kun Wang, Guibin Zhang, ManKit Ye +6

The past two years have witnessed the meteoric rise of Large Language Model (LLM)-powered multi-agent systems (MAS), which harness collective intelligence and exhibit a remarkable…