mlsanityData to 7 Oct 2026

Wormhole Memory: A Rubik's Cube for Cross-Dialogue Retrieval

arXiv 2501.14846 ↗First posted 24 Jan 2025cs.LG cs.AI cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

In view of the gap in the current large language model in sharing memory across dialogues, this research proposes a wormhole memory module (WMM) to realize memory as a Rubik's cube that can be arbitrarily retrieved between different dialogues. Through simulation experiments, the researcher built an experimental framework based on the Python environment and used setting memory barriers to simulate the current situation where memories between LLMs dialogues are difficult to share. The CoQA development data set was imported into the experiment, and the feasibility of its cross-dialogue memory retrieval function was verified for WMM's nonlinear indexing and dynamic retrieval, and a comparative analysis was conducted with the capabilities of Titans and MemGPT memory modules. Experimental results show that WMM demonstrated the ability to retrieve memory across dialogues and the stability of quantitative indicators in eight experiments. It contributes new technical approaches to the optimization of memory management of LLMs and provides experience for the practical application in the future.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 26 of its 42 references that are in the map. First posted on arXiv 24 Jan 2025.

Builds on

26 of 42 references.

References · 26

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2022FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awarenesscited by 3,611
  4. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  5. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,295
  6. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  7. 2018CoQA: A Conversational Question Answering Challengecited by 674
  8. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  9. 2023MemoryBank: Enhancing Large Language Models with Long-Term Memorycited by 539
  10. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 491
  11. 2024Titans: Learning to Memorize at Test Timecited by 303
  12. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 191
14 more
  1. 2023Augmenting Language Models with Long-Term Memorycited by 186
  2. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 95
  3. 2024Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Modelscited by 71
  4. 2024A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directionscited by 69
  5. 2023A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challengecited by 55
  6. 2023DTrOCR: Decoder-only Transformer for Optical Character Recognitioncited by 40
  7. 2023Empowering Working Memory for Large Language Model Agentscited by 18
  8. 2024From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalitiescited by 18
  9. 2022LSG Attention: Extrapolation of pretrained Transformers to long sequencescited by 16
  10. 2024Merging Text Transformer Models from Different Initializationscited by 16
  11. 2017Memory Augmented Neural Networks with Wormhole Connectionscited by 15
  12. 2024Human-inspired Perspectives: A Survey on AI Long-term Memorycited by 12
  13. 2024The Battle of LLMs: A Comparative Study in Conversational QA Taskscited by 5
  14. 2024Adapting LLaMA Decoder to Vision Transformercited by 3

Built on by

Not cited yet.