3 papers
cs.AI2026
MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection
Zhewen Tan, Yilun Yao, Huiyan Jin +9
Large language model agents increasingly rely on persistent memory to store past interactions, retrieve relevant demonstrations, and improve long-horizon task execution. However, t…
cs.AI2026
Echo: Learning from Experience Data via User-Driven Refinement
Hande Dong, Xiaoyun Liang, Jiarui Yu +15
Static "human data" faces inherent limitations: it is expensive to scale and bounded by the knowledge of its creators. Continuous learning from "experience data" - interactions bet…
cs.CL2024
Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models
Fengchen Liu, Jordan Jung, Wei Feinstein +2
This paper introduces a novel approach to enhancing closed-domain Question Answering (QA) systems, focusing on the specific needs of the Lawrence Berkeley National Laboratory (LBL)…