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hugging-face daily papers

Fetch and digest HuggingFace Daily Papers. Use when user asks for today's HF papers, daily paper digest, wants a paper report, or says 论文精选/今日论文/HF daily pap...
获取并整理HuggingFace每日论文。当用户询问今天的HF论文、每日论文摘要、想要论文报告,或说“论文精选/今日论文/HF daily pap...”时使用。
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概述

HF Daily Papers

Fetch papers from HuggingFace Daily Papers feed and generate a digest with analysis.

Setup: Get Your HF Token

  1. Go to https://huggingface.co/settings/tokens
  2. Create a Read token (any name)
  3. Set the token as an environment variable:
# Windows PowerShell
$env:HF_TOKEN = "hf_xxxxxxxxxxxxx"

# macOS / Linux / Git Bash
export HF_TOKEN="hf_xxxxxxxxxxxxx"

> The script reads HF_TOKEN from os.environ. If not set, it exits with a clear error message.

Step 1: Run the fetcher

cd <skill-path>/scripts && python hf_papers.py [date YYYY-MM-DD]
  • No date arg = yesterday
  • Output: hf_results.json (saved in the working directory)

Step 2: Read results

Read hf_results.json. Fields:

FieldDescription
--------------------
paperIdarXiv ID
titlePaper title
votesCommunity upvotes
submittedBySubmitter name
organizationResearch institution
summaryFull abstract (cleaned, up to 2000 chars)
aiSummaryAI-generated summary (200-300 chars, from HF blue box)
githubRepoGitHub repo URL if available
keywordsAI-extracted keywords (up to 10)
linkHF paper page
arxivLinkarXiv abstract page

Step 3: Score and write digest

Scoring reference (10-point scale, intuition-based):

DimensionWeightBonus signals
----------------------------------
Innovation0-3New benchmark/dataset, novel direction, first-of-its-kind
Practicality0-3Has GitHub code, clear real-world application, big tech/academia
Technical depth0-2Summary >200 chars, contains RL/MCTS/evolutionary methods
Interestingness0-2Provocative thesis, cross-discipline, counterintuitive

High vote count (>10) is a bonus — reflects community heat.

Step 4: Output format

📄 HF Daily Papers · [date]  N papers total

## 🔴 Must Read (score 8-10)
[Title | ID | Organization
 Xiaolongxia comment: ...]
## 🟡 Worth Noting (score 6-7)
[Compact list + one-line evaluation]
## 🟢 Skim If Interested
[Ultra brief list]

## 🦞 Summary
Top 3 + today's main theme observations

Commentary guidelines:

  • Every "Must Read" paper needs a "Xiaolongxia comment" — explain the core insight in your own words
  • Say why it's worth reading and what makes it special
  • Can connect to other papers or industry trends
  • Tone: casual, witty, friendly — like chatting with a friend
  • "Worth Noting" entries: one sentence max

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-05-07 11:54 安全 安全

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