paper-with-me

홈 › Papers

MEMAUDIT: An Exact Package-Oracle Evaluation Protocol for Budgeted Long-Term LLM Memory Writing

2026-05-04 · Nishant Bhargava, Rodrigo Sobral Barrento arxiv

Long-term LLM agents must compress streams of past interactions into persistent memory before future queries are known. Existing evaluations usually measure final question-answering accuracy, which entangles memory writing with retrieval, prompting, and reader reasoning. We introduce MEMAUDIT, an exact packageoracle evaluation protocol for budgeted long-term memory writing. A MEMAUDIT package fixes an experience stream, candidate memory representations, storage costs, semantic evidence units, future-query requirements, and a budget, turning write-time memory selection into a finite auditable optimization problem with a certified denominator. We instantiate this protocol with a concave-over-modular semantic coverage objective under storage and one-representation-per-experience constraints, and compute exact package optima using branch-and-bound with MILP certification. Across controlled exact packages, validity-heavy stress tests, human-audited natural support slices, and exported Mem0, A-Mem, and Letta stores, MEMAUDIT separates representation quality, validity-state preservation, and budget-aware selection effects that end-to-end QA cannot localize. The resulting artifact provides reusable package generators, certified solvers, natural package exports, external-system scorers, and cached reproducibility metadata for evaluating what memory writers actually preserve under fixed storage budgets.

📄 PDF Abstract BibTeX arXiv:2605.02199

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection

2026-05-22 · Zhewen Tan, Yilun Yao, Huiyan Jin, Wenhan Yu 외 arxiv

Large language model agents increasingly rely on persistent memory to store past interactions, retrieve relevant demonstrations, and improve long-horizon task execution. However, this memory mechanism also creates a prac…

Anomaly Detection

Empirical Software Engineering TerraProbe: A Layered-Oracle Framework for Detecting Deceptive Fixes in LLM-Assisted Terraform

2026-06-25 · Manar Alsaid, Chimdumebi Nebolisa, Faris Abbas arxiv

Security misconfigurations in Terraform Infrastructure-as-Code are a growing risk in cloud deployments, and large language models are increasingly used as automated repair agents. Existing evaluations often treat a repai…

Guideline-as-Oracle: Zero-Annotation Training of an Ophthalmic Telephone Triage Agent

2026-08-05 · Chenyu Wang, Yi Liu, Baoqing Li, Min Tu 외 arxiv

Scaling supervision for multi-turn medical agents is difficult because expert dialogue annotation is costly and clinical conversations are privacy-restricted. We introduce Guideline-as-Oracle (GAO), which compiles Americ…

Structured Security Auditing and Robustness Enhancement for Untrusted Agent Skills

2026-04-28 · Lijia Lv, Xuehai Tang, Jie Wen, Jizhong Han 외 arxiv

Agent Skills package SKILL.md files, scripts, reference documents, and repository context into reusable capability units, turning pre-load auditing from single-prompt filtering into cross-file security review. Existing g…

AMIGO: Agentic Multi-Image Grounding Oracle Benchmark

2026-03-30 · Min Wang, Ata Mahjoubfar arxiv

Agentic vision-language models increasingly act through extended interactions, but most evaluations still focus on single-image, single-turn correctness. We introduce AMIGO (Agentic Multi-Image Grounding Oracle Benchmark…

Question Selection