Hacker News·2 min read·hard

Zero-Mem: Zero-Token Memory Operations for LLM Agents

T
theanonymousone
Zero-Mem: Zero-Token Memory Operations for LLM Agents
AI Summary

Researchers have introduced Zero-Mem, a new method for LLM agents to perform memory operations without consuming additional tokens. This approach aims to improve the efficiency and scalability of memory management in artificial intelligence systems.

Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yilin Xiao [ view email ] [v1] Fri, 31 Jul 2026 13:01:06 UTC (414 KB) Full-text links: Access Paper: View a PDF of the paper titled Zero-Mem: Zero-Token Memory Operations for LLM Agents, by Yilin Xiao and 10 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.CL < prev | next > new | recent | 2026-07 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Continue reading on Headlinne

Create a free account to read the full article.

Read full article →
technologyscience

Get the full story

Sign up for Headlinne to unlock AI insights, political bias analysis, and your personalized news feed.

Create free account

Already have an account? Sign in