1.4 KiB
1.4 KiB
Paper: Memory-Augmented Vision-Language Agents for Persistent and Semantically Consistent Object Captioning
type: paper title: Memory-Augmented Vision-Language Agents for Persistent and Semantically Consistent Object Captioning authors: Tommaso Galliena, Stefano Rosa, Tommaso Apicella, Pietro Morerio, Alessio Del Bue, Lorenzo Natale year: 2026 venue: arXiv url: https://arxiv.org/abs/2603.24257 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-03-25 updated_at: 2026-03-30 status: queued relevance: high topics:
- agent-evaluation
- embodied-agent
- memory methods:
benchmarks:
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datasets:
- cs.CV related_concepts:
related_jobs:
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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, embodied-agent, memory
- arXiv categories: cs.CV
- 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?