# 2022hpsk/SpeakerMemR1

> A memory framework for multi-party dialogue: it stores utterances verbatim with speaker labels and builds structured person- and group-level states to answer questions over long conversations. Includes an inference package, benchmark runners, and Writer-model training recipes.

- Magnitude: 1.8 out of 10 — Steady
- Stars: 82 total · +0 stars today, ≈ 9 by evening
- Star trust: star growth looks organic
- Category: Language models · Language: Python · License: MIT · Created: 2026-09-20 · Last push: 2026-09-24
- GitHub: https://github.com/2022hpsk/SpeakerMemR1 · Homepage: https://2022hpsk.github.io/SpeakerMemR1/ · Page: https://gitnova.dev/en/r/2022hpsk/SpeakerMemR1

## Useful for

- Run evaluation on GroupMemBench, SocialMemBench, or EverMemBench with the provided runners
- Train a Qwen2.5-3B Writer with SpeakerLevenshtein rewards for local memory writing
- Compare memory quality against BM25 and dense baselines via run_baseline.py

## Why it’s here

- 0 stars so far today, about 9 expected by the end of the day.
- The spike has held for 2 days in a row — not a one-off blip.
- The repository is 6 days old and already has 82 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #162.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 13
- Issues and pull requests: 0
- Watchers: 0
- Average over the last week: 13 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 1

## Stars per day, last 7 days (oldest → newest, today is partial)

2026-09-20 … 2026-09-26: 1, 1, 66, 2, 0, 12, 0

## Spotted in now

- Top new repositories this week: #162

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-09-26 03:18 UTC, updated every 30 minutes.