Memory has emerged as a cornerstone of modern LLM-based agents, supporting their evolution from single-turn assistants to long-term collaborators. However, memory is not always beneficial: retrieved memories often induce a critical issue of sycophancy, causing agents to over-align with the user at the cost of factual accuracy or objective reasoning.
arXiv:2607. 01071v1 Announce Type: cross Abstract: Memory has emerged as a cornerstone of modern LLM-based agents, supporting their evolution from single-turn assistants to long-term collaborators.
By Zhishang Xiang, Zerui Chen, Yunbo Tang, Zhimin Wei, Ruqin Ning, Yujie Lin, Qinggang Zhang, Jinsong Su
The paper investigates how persistent memory in AI agents can lead to over‑trust in stale facts, creating a "Memory Trust Gap" that worsens as model capability increases. Using a benchmark with Benefit and Safety suites across Qwen3 models of varying sizes, the authors show that larger models are more prone to harmful over‑trust, especially when metadata is absent or misleading. They also demonstrate that mitigation strategies such as exposing metadata or pre‑resolving conflicts improve accuracy, but the effectiveness depends on model size and dataset.
By Jundong Hu, Shekar Ramachandran
arXiv:2606. 29279v1 Announce Type: cross Abstract: LLM agents carry conclusions across steps and sessions in compressed memory, and memory products (e.
By Alex Kwon
The paper reports on a series of experiments examining how different forms of directives—such as record pointers, criteria, or combinations—affect an agent’s choice of archived source records when it inherits six one-line memories. Across twelve registered studies involving 14,760 attempts on a single instrument lineage, the authors measured the impact of various directive formats on six direct-provider models, nine OpenRouter-served models, and several Claude and Opus 5 models, noting differences in performance metrics and replication outcomes. The results are purely descriptive, detailing the effects of exact edits on fixed panels with registered intervals and no claim of underlying mechanisms.
By Kazuki Nakayashiki
arXiv:2605.12978v2 Announce Type: replace
Abstract: Learning from past experience benefits from two complementary forms of memory: episodic traces -- raw trajectories of what happened -- and consolid...
By Dylan Zhang, Yanshan Lin, Zhengkun Wu, Yihang Sun, Bingxuan Li, Dianqi Li, Hao Peng