most citedMemory in the Age of AI Agents

1 citations · 1 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2026

JIT-Agent: Scaling Harness Intelligence via Just-in-Time Harness Evolution

Guibin Zhang, Leo Lu, Fangzhou Xie +15

Agent capability is not determined by the model alone. The agent harness, encompassing memory management, planning strategy, action protocol, and tool/skill orchestration, can domi…

cs.AI2026

LLM-based Agents for Forecasting and Prediction: Methods, Training, Evaluation, and Applications

Xiaogang Xu, Jiaqi Tang, Jianmin Chen +12

Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external tools, and iterative prediction.…

cs.CV2026

Quo Vadis, World Modeling?

Yu Yang, Xuemeng Yang, Licheng Wen +17

Continually improving agents require dynamic interaction feedback beyond static supervision, yet direct real-environment interaction is costly, slow, unsafe, and hard to paralleliz…

cs.AI2026

DOPD: Dual On-policy Distillation

Xinlei Yu, Gen Li, Qingyi Si +13

On-policy distillation (OPD) offers superior capacity transfer by supervising student-sampled trajectories with dense token-level signals. To furnish high-quality supervision sourc…

cs.CV2026

MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection

Xiaobin Hu, Haoyang He, Bo Yin +5

While recent advancements in anomaly detection have demonstrated the efficacy of CNN- and Transformer-based approaches, these architectures face inherent limitations: CNNs struggle…

cs.CL2026

OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation

Guibin Zhang, Xun Xu, Yanwei Yue +4

Memory has become a standard substrate for self-evolving agents, yet retaining experience is not the same as learning how to evolve through it. Existing memory agents can store tra…

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.AI2026

Dual Latent Memory for Visual Multi-agent System

Xinlei Yu, Chengming Xu, Zhangquan Chen +8

While Visual Multi-Agent Systems (VMAS) promise to enhance comprehensive abilities through inter-agent collaboration, empirical evidence reveals a counter-intuitive "scaling wall":…

cs.CL2026★ 1 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

IRPO: Boosting Image Restoration via Post-training GRPO

Haoxuan Xu, Yi Liu, Tianfu Li +7

Post-training has become effective for high-level generation, but its role in low-level vision remains underexplored. Existing image restoration methods often rely on fixed pixel-w…

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…