most citedMemory in the Age of AI Agents

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 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.CL2026

SAGE Celer 2.6 Technical Card

SAGEA Research Team, Basab Jha, Firoj Paudel +8

We introduce SAGE Celer 2.6, the latest in our line of general-purpose Celer models from SAGEA. Celer 2.6 is available in 5B, 10B, and 27B parameter sizes and benefits from extensi…

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.AI2026

SAGE-32B: Agentic Reasoning via Iterative Distillation

Basab Jha, Firoj Paudel, Ujjwal Puri +6

We demonstrate SAGE-32B, a 32 billion parameter language model that focuses on agentic reasoning and long range planning tasks. Unlike chat models that aim for general conversation…

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…

cs.CL2025

AgenTracer: Who Is Inducing Failure in the LLM Agentic Systems?

Guibin Zhang, Junhao Wang, Junjie Chen +3

Large Language Model (LLM)-based agentic systems, often comprising multiple models, complex tool invocations, and orchestration protocols, substantially outperform monolithic agent…