most citedMemory in the Age of AI Agents

1 citations · 2 across the 9 of their papers we have counts for

collaborators

11 papers

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

MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

Fangda Ye, Yuxin Hu, Pengxiang Zhu +19

Recent progress in deep research systems has been impressive, but evaluation still lags behind real user needs. Existing benchmarks predominantly assess final reports using fixed r…

cs.LG20261 cited

Slow-Fast Inference: Training-Free Inference Acceleration via Within-Sentence Support Stability

Xingyu Xie, Zhaochen Yu, Yue Liao +3

Long-context autoregressive decoding remains expensive because each decoding step must repeatedly process a growing history. We observe a consistent pattern during decoding: within…

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.CL2026

EvoRoute: Experience-Driven Self-Routing LLM Agent Systems

Guibin Zhang, Haiyang Yu, Kaiming Yang +4

Complex agentic AI systems, powered by a coordinated ensemble of Large Language Models (LLMs), tool and memory modules, have demonstrated remarkable capabilities on intricate, mult…

cs.CL2025

MemEvolve: Meta-Evolution of Agent Memory Systems

Guibin Zhang, Haotian Ren, Chong Zhan +5

Self-evolving memory systems are unprecedentedly reshaping the evolutionary paradigm of large language model (LLM)-based agents. Prior work has predominantly relied on manually eng…