arXiv AI June 17, 2026 By Josef Liyanjun Chen

Memory as a Wasting Asset: Pricing Flash Endurance for Embodied Agents, and the Limits of Doing So

arXiv:2606. 18144v1 Announce Type: new Abstract: A robot's flash endurance is a non-renewable stock: every persisted write spends one of a few thousand program/erase cycles and never refills, yet no fielded robot memory system prices which memories are worth an erase cycle.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Aug 18

Don't Drop the BATON: Long-Horizon Robot Manipulation via Agentic Subtask Exploration and Transition-aware Memory

arXiv:2608. 16889v1 Announce Type: cross Abstract: Long-horizon robot manipulation chains many contact-rich skills into one multi-stage task.

By Bingxin Xu, Yuzhang Shang, Emilio Ferrara

llms agents robotics multimodal benchmarks

arXiv AI

Jun 3

AURA: Action-Gated Memory for Robot Policies at Constant VRAM

arXiv:2606. 02775v1 Announce Type: new Abstract: The KV-cache is the right memory for datacenters but the wrong memory for robots.

By Josef Chen

agents robotics multimodal benchmarks

Hugging Face Trending Papers

Aug 17

Don't Drop the BATON: Long-Horizon Robot Manipulation via Agentic Subtask Exploration and Transition-aware Memory

Long-horizon robot manipulation chains many contact-rich skills into one multi-stage task. Vision-language-action (VLA) models increasingly master the individual skills, yet the chain still fails: err...

llms agents robotics multimodal benchmarks

arXiv AI

Jul 21

Memory in the Loop: In-Process Retrieval as Extended Working Memory for Language Agents

arXiv:2607. 05690v2 Announce Type: replace Abstract: Language agents run a loop - observe, reason, act - but the memory they reason over sits outside it: a store queried at most once per turn.

By Yusuf Khan, Carlo Lipizzi

llms rag agents

arXiv Machine Learning

Jun 25

Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory

arXiv:2606. 25115v1 Announce Type: new Abstract: On-device language-model agents improve by accumulating experience in retrieved memory rather than by updating weights.

By Beining Wu, Zihao Ding, Jun Huang, Yanxiao Zhao

llms agents robotics benchmarks

arXiv AI

Jul 8

Memory in the Loop: In-Process Retrieval as ExtendedWorking Memory for Language Agents

arXiv:2607. 05690v1 Announce Type: new Abstract: Language agents run a loop - observe, reason, act - but the memory they reason over sits outside it: a store queried at most once per turn.

By Yusuf Khan, Carlo Lipizzi

llms rag agents

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Don't Drop the BATON: Long-Horizon Robot Manipulation via Agentic Subtask Exploration and Transition-aware Memory

AURA: Action-Gated Memory for Robot Policies at Constant VRAM

Don't Drop the BATON: Long-Horizon Robot Manipulation via Agentic Subtask Exploration and Transition-aware Memory

Memory in the Loop: In-Process Retrieval as Extended Working Memory for Language Agents

Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory

Memory in the Loop: In-Process Retrieval as ExtendedWorking Memory for Language Agents