1.3 KiB
1.3 KiB
Paper: Rosetta Memory: Adaptive Memory for Cross-LLM Agents
type: paper title: "Rosetta Memory: Adaptive Memory for Cross-LLM Agents" authors: Hao Yang, Shiqi Shen, Haoxuan Li, Zhipeng Wang, Zhi Gong, Xu Chen year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.07711 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-05 updated_at: 2026-06-05 status: queued relevance: high topics:
- coding-agent
- memory
- planning
- reasoning methods:
benchmarks:
models:
datasets:
- cs.LG
- cs.AI related_concepts:
related_jobs:
related_experiments:
related_projects:
collection_score: 17 collection_queries: planning-agent
One-line Takeaway
Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.
Why Collected
- matched queries: planning-agent
- inferred topics: coding-agent, memory, planning, reasoning
- arXiv categories: cs.LG, 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
queuedtoskimmedorsummarized?