Signals 4 · free daily AI digest

Measure Before You Manage: Evaluating Agent Working Memory in Coding Agents

Paper recorded by Signals 4 on 2026-08-31 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-31 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.AI · 人工智能 · first seen 2026-09-01

Abstract

Agent working memory is heterogeneous. Objects such as instructions, artifacts, tool outputs, and agent-generated state play different semantic roles and exhibit different size, retention, and representation profiles. Recent work has begun to explore memory-management mechanisms that account for such heterogeneity. This work focuses on semantic heterogeneity and studies how it should shape the man

Read on arXiv →

#254 most recent of 300 cs.AI papers we have recorded · ↑ newer: Wrong Prediction, Right Answer: Recovering Evidence from Collapsed LLM · ↓ older: MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents
Cite this page: Measure Before You Manage: Evaluating Agent Working Memory in Coding Agents: the #254 most recent of 300 cs.AI papers we have recorded (as of 2026-08-31). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/measure-before-you-manage-evaluating-agent-working-memory-in-coding-agents.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions