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Beyond Downstream QA: Rethinking How We Evaluate Agent Memory

Paper recorded by Signals 4 on 2026-10-15 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-15 on arXiv · recorded by Signals 4 on 2026-10-16

Category: cs.CL · 自然语言处理 · first seen 2026-10-16

Abstract

Agent memory benchmarks evaluate whether an agent's responses reflect correct knowledge, measuring downstream question-answering accuracy as a proxy for memory quality. We show this evaluation paradigm is incomplete: it conflates memory correctness with retrieval and generation quality, producing both false positives where correct responses mask broken memory and false negatives where incorrect re

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#239 most recent of 660 cs.CL papers we have recorded · ↑ newer: Training-Free On-Policy Distillation · ↓ older: Hy-Memory-30B-A3B: Attributed Reinforcement Learning for Long-Term Mem
Cite this page: Beyond Downstream QA: Rethinking How We Evaluate Agent Memory: the #239 most recent of 660 cs.CL papers we have recorded (as of 2026-10-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/beyond-downstream-qa-rethinking-how-we-evaluate-agent-memory.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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