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The official implementation of the paper "Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models" (NeurIPS 2025 Poster).

active 2025-09-222026-03-15 (UTC)

Complete coverage26,352 / 26,352 hourly files (100%) · 2 absent upstream2023-08-152026-08-16 (UTC)
Events
41
Pushes
4
Pull requests
0
Issues
4
Stars
25
Forks
2

Activity over time

Daily event counts in the loaded window

Line chart, 175 days from 2025-09-22 to 2026-03-15. Pushes: 4 total, peak 3 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 4 total, peak 1 in a day. Comments: 3 total, peak 1 in a day. Stars: 25 total, peak 3 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
Clover-Hill11403

Recent activity

Latest issues, pull requests and releases

  • Issue#5Clover-Hill2025-12-27 09:48
    生成Wikitext-103 datastore是否需要大量存储空间
  • Issue#4Clover-Hill2025-12-04 23:33
    Can Memory Decoding be adapted to Speculative Decoding?
  • Issue comment#4Clover-Hill2025-12-03 15:04
    Can Memory Decoding be adapted to Speculative Decoding?
  • Issue#2Clover-Hill2025-11-29 18:48
    关于训练脚本
  • Issue comment#2Clover-Hill2025-11-29 06:52
    关于训练脚本
  • Issue#1Clover-Hill2025-11-26 17:04
    生成embedding的模型在wiki-103上预训练过,这个地方有做过消融吗?如果我不做预训练呢
  • Issue comment#1Clover-Hill2025-11-26 17:04
    生成embedding的模型在wiki-103上预训练过,这个地方有做过消融吗?如果我不做预训练呢

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 25 stars here means stars gained during the window, not the repo's star count.