agent/papers/items/2026-2606-10616-learning-what-to-remember-observability-safe-memory-retention-via-constrained-op.md

Paper: Learning What to Remember: Observability-Safe Memory Retention via Constrained Optimization for Long-Horizon Language Agents

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type: paper title: "Learning What to Remember: Observability-Safe Memory Retention via Constrained Optimization for Long-Horizon Language Agents" authors: Qingcan Kang, Liu Mingyang, Shixiong Kai, Kaichao Liang, Tao Zhong, Mingxuan Yuan year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.10616 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-09 updated_at: 2026-06-29 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• memory
• planning
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 17 collection_queries: language-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: language-agent
• inferred topics: agent-evaluation, computer-use, memory, planning, reasoning, tool-use
• arXiv categories: cs.AI
• collection score: 17

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.10616