# Weekday Hugging Face paper briefing for your ML team

> Every weekday at 7am, the day's new AI papers get filtered down to the topics your team actually works on, archived in Notion, and the top three land in Slack.

- Workflow type: agent
- Services: Hugging Face, Notion, Slack Bot
- Categories: Engineering
- Published: 2026-08-04

## What it does

- Picks up the day's curated Hugging Face papers every weekday morning, before your team starts reading
- Keeps only the papers that touch your topics, such as retrieval, evaluation, efficient inference, and agents, and drops the rest
- Writes a two sentence plain English take on each paper: what is actually new, and what it changes for someone building with it
- Files the full briefing as a dated Notion page so the archive stays searchable, then posts the top three to Slack with a link to the rest

## What you'll need

- A Hugging Face account, a free one is fine
- A Notion workspace, plus a parent page where the daily briefings should be filed
- A Slack workspace and the channel your ML team actually reads
- A short list of the research topics your team cares about

## Prompt

Every weekday at 7am, pull the day's curated papers from Hugging Face using Get Daily Papers. For each paper, keep the title, the authors, the abstract, and the upvote count.

Then filter down to the topics my ML team actually works on. The topic list is retrieval, evaluation, efficient inference, and agents. Treat this list as the main setting to edit: keep it in one obvious place, because it is the thing I will tune most often. Drop every paper that does not fit one of these topics, and never pad the briefing to reach a certain length. A short briefing is a good briefing. Some days only two or three papers survive the filter, and that is the correct outcome.

For every paper I keep, write a two sentence plain English summary. The first sentence says what is actually new. The second says why a practitioner should care, meaning what specifically changes for someone building with this. Tag each paper with the topic it matched. Keep the register practitioner focused rather than academic: do not restate the abstract in fancier words, and skip benchmark tables unless a particular number is the whole point of the paper.

Create a dated Notion page with Create a Page holding the full briefing, so the archive becomes searchable over time. Put the date in the page title so the pages sort and scan cleanly, and file every briefing under the same parent page. The Notion page holds every paper that passed the filter, grouped by topic tag, each with its title, authors, upvote count, my two sentence summary, and a link to the paper on Hugging Face.

Then post the top three papers by upvote count to Slack with Send a Message, sending as the bot so the briefing keeps running regardless of who set it up. Each of the three gets its title, its topic tag, its upvote count, and its two sentence summary. Close the message with a link to the Notion page so the team can read the rest there.

If no papers clear the topic filter on a given day, still create the Notion page noting that nothing matched, and post a single short line to Slack saying there is nothing relevant today. I would rather see an honest quiet day than an empty or padded briefing.

## How to customize

- The topic list is the main knob: swap retrieval, evaluation, efficient inference, and agents for whatever your team works on
- Change the time or the days it runs, though weekday mornings match the source, which does not publish on weekends
- Adjust how many papers go to Slack, or point the briefing at a different channel

## Example output

Today's ML briefing. 3 of 11 papers matched your topics.

1. Retrieval | Late interaction reranking without the memory blowup (142 upvotes)
Compresses ColBERT style token vectors so a reranker fits in a fraction of the usual index size. If you shelved late interaction because serving the index was too expensive, this makes it affordable again.

2. Efficient inference | Speculative decoding that adapts its draft length (98 upvotes)
Varies how far the draft model runs ahead based on how well it is currently agreeing with the target model. A straight throughput win on existing serving stacks with no retraining required.

3. Agents | A long horizon tool use benchmark that is not yet saturated (76 upvotes)
Tasks run thirty or more tool calls deep, where today's agents degrade badly. Useful as a regression test if you ship agents and your current evals all sit at 95 percent.

Full briefing with the other 8 papers: [Notion page link]

## FAQ

### Why only weekdays?

The Hugging Face daily papers list is curated and does not publish on weekends, so a weekday schedule matches the source. You will not get empty Saturday briefings.

### Can I change which topics it watches?

Yes, and it is designed for that. The topic list is the one setting most teams edit. Replace the starting topics with your own, whether that is multimodal models, safety, fine tuning, or anything else, and the filter follows.

### What happens if no papers match my topics that day?

You get a short note saying nothing relevant came up, rather than a padded briefing full of papers you do not care about. A quiet day is a real signal.

### How is this different from just subscribing to the Hugging Face papers email?

The email sends the raw list. This filters that list down to your topics and rewrites each paper in practitioner terms, so you read five relevant summaries instead of skimming thirty abstracts.

### Do I need a paid Hugging Face or Notion plan?

No. A free Hugging Face account and a standard Notion workspace are enough. You do need to give the connection access to the Notion page where briefings get filed.

### Will the summaries just repeat the abstract?

No, that is the point of the setup. Each summary is written to say what is genuinely new and what changes for someone building with it, in plain English rather than academic phrasing.

Use this prompt in General Input: https://www.generalinput.com/prompts/weekday-hugging-face-paper-briefing-for-your-ml-team