← Knowledge

◇ Paper · OmniScientist: An Omni-Modal Omni-Discipline AI Scientist

Plainly

This is a lead card for today's AI paper: what it covers, who wrote it, and where to read it.

Editor's verdict

Use as a today's-frontier lead; read the paper to reproduce experiments.

Derived from structured fields · Confidence: medium (functionality not individually tested)

Open official site / source ↗
Key facts · machine-readable
Official / sourcehttps://huggingface.co/papers/2608.13558
Chinese editor copy (original, collapsed)

① 这是什么

今日论文《今日论文 · OmniScientist: An Omni-Modal Omni-Discipline AI Scientist》（Bobo Li、Hao Fei、Tianjie Ju、Mong-Li Lee、Wynne Hsu），来自 HF Daily Papers 公开源。

② 值不值得用

进入 HF 每日精选说明有社区关注度；是否与你的问题相关需要读原文判断，本条目不评价研究质量。

③ 怎么开始

先读摘要，需要再读全文（https://huggingface.co/papers/2608.13558）；对照论文 ID（2608.13558）可找实现与讨论。

④ 关键证据

  • 论文 ID 2608.13558
  • 作者 Bobo Li、Hao Fei、Tianjie Ju、Mong-Li Lee、Wynne Hsu

⑤ 注意事项与坑

摘要来自作者原文，未做同行评议级核验；引用请以正式发表版本为准。

One-line premise

Best for: readers tracking today's AI research frontier.

Consider if: you need to reproduce full experimental details (read the paper).

Status: machine-checked (structure & source validation); functionality not individually tested.

Minimal verification (3 steps)

  1. Read abstract — OmniScientist: An Omni-Modal Omni-Discipline AI Scientist
  2. Check authors/date — Bobo Li, Hao Fei, Tianjie Ju · 2026-08-13
  3. Run CLI — npx aiskillready search 13558
Quick start

Use it like this

npx aiskillready search 13558   # official CLI, verified runnable (aiskillready@0.2.0)

Note: `npx aiskillready` is this site's published CLI (npm aiskillready@0.2.0) — verified runnable; third-party commands are given per official docs and not individually tested. We don't fabricate conclusions.

Glossary: what are SKILL.md / veridrop / schema? (expand)
Trust layer: machine check / cost / confidence / schema (expand)

Entry ID: ASR-PAPER-20260820-2608-13558 ｜ Type: Paper ｜ schema v0.5

✅ machine-checked pass 💰 Enrichment cost $0.0000 🧭 Confidence medium 📌 schema 0.5 🛂 Review agent reviewed 🧪 Functionality unverified (Top-20 manual testing planned)

Related (what you should know)

Related (3) · expand
Similar

◇ Paper · Scaling Creative Writing Beyond Story-Centric Data with Attribute-Guided Genre Expansion

Scaling Creative Writing Beyond Story-Centric Data with Attribute-Guided Genre Expansion. by Hwan Chang, Yongil Kim, Heuiyeen Yeen, Yireun Kim, Jinsik Lee, Hwanhee Lee. published 2026-08-14.

 Similar

◇ Paper · Training Leaves Traces: Centered Residual Signatures for Language Model Lineage Verification

Training Leaves Traces: Centered Residual Signatures for Language Model Lineage Verification. by Aman Singh Thakur, Rayan Khoury. published 2026-08-14.

 Similar

◇ Paper · Zetta ζ: An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence

Zetta ζ: An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence. by Xin Ding, Liang Mi, Mingzhe Huang, Zixuan Wang, Chao Zhang, Zixu Hao, Fu Chen, Xiangyu Li, Yikai Zheng, Yaoyu Guo, Weiju. published 2026-08-17.

Feedback

Something wrong / command failed? File an issue with the entry ID; it feeds back into the next revision.

🐞 Report an issue →
AI block · machine-readable (same source of truth)
AI block · machine-readable JSON (click to expand) 
{
  "schema_version": "0.5",
  "entry_id": "ASR-PAPER-20260820-2608-13558",
  "record_type": "paper",
  "title": "今日论文 · OmniScientist: An Omni-Modal Omni-Discipline AI Scientist",
  "observed_at": "2026-08-20",
  "source": {
    "name": "huggingface.co/api/daily_papers",
    "url": "https://huggingface.co/api/daily_papers?limit=10",
    "snapshot_hash": "d637c477ff6da03cf6c527f6d81da12836edef97191c108db740c2967537d66e",
    "fetched_at": "2026-08-20T04:51:45+00:00"
  },
  "confidence": "medium",
  "human_stream": {
    "summary": "Recent advances in foundation models have enabled AI scientists to automate increasingly complete research workflows, from hypothesis generation and code execution to manuscript preparation. Yet workflow coverage alone does not provide access to the full evidence on which scientific discovery depends. Existing systems typically reason over text, code, labels, or precomputed summaries, leaving scie",
    "key_points": [
      "论文 ID 2608.13558",
      "作者 Bobo Li、Hao Fei、Tianjie Ju、Mong-Li Lee、Wynne Hsu",
      "发布 2026-08-13T00:00:00.000Z"
    ],
    "note": "来源为 HuggingFace daily papers 公开 API；完整阅读请走原文链接。",
    "what_it_is": "今日论文《今日论文 · OmniScientist: An Omni-Modal Omni-Discipline AI Scientist》（Bobo Li、Hao Fei、Tianjie Ju、Mong-Li Lee、Wynne Hsu），来自 HF Daily Papers 公开源。",
    "worth_it": "进入 HF 每日精选说明有社区关注度；是否与你的问题相关需要读原文判断，本条目不评价研究质量。",
    "how_to_start": "先读摘要，需要再读全文（https://huggingface.co/papers/2608.13558）；对照论文 ID（2608.13558）可找实现与讨论。",
    "evidence": [
      "论文 ID 2608.13558",
      "作者 Bobo Li、Hao Fei、Tianjie Ju、Mong-Li Lee、Wynne Hsu"
    ],
    "cautions": "摘要来自作者原文，未做同行评议级核验；引用请以正式发表版本为准。"
  },
  "ai_stream": {
    "structured": {
      "paper_id": "2608.13558",
      "title": "OmniScientist: An Omni-Modal Omni-Discipline AI Scientist",
      "authors": [
        "Bobo Li",
        "Hao Fei",
        "Tianjie Ju",
        "Mong-Li Lee",
        "Wynne Hsu"
      ],
      "published_at": "2026-08-13T00:00:00.000Z",
      "url": "https://huggingface.co/papers/2608.13558",
      "source_label": "hf-daily-papers"
    },
    "raw": [
      {
        "paper_id": "2608.13558",
        "title": "OmniScientist: An Omni-Modal Omni-Discipline AI Scientist",
        "authors": [
          "Bobo Li",
          "Hao Fei",
          "Tianjie Ju",
          "Mong-Li Lee",
          "Wynne Hsu"
        ],
        "summary": "Recent advances in foundation models have enabled AI scientists to automate increasingly complete research workflows, from hypothesis generation and code execution to manuscript preparation. Yet workflow coverage alone does not provide access to the full evidence on which scientific discovery depends. Existing systems typically reason over text, code, labels, or precomputed summaries, leaving scientifically decisive spatial, temporal, cross-channel, and procedural relations unavailable to the agent. We introduce OmniScientist, an end-to-end, omni-modal AI scientist that conducts multidisciplin",
        "published_at": "2026-08-13T00:00:00.000Z",
        "submitted_on_daily_at": null,
        "url": "https://huggingface.co/papers/2608.13558"
      }
    ]
  },
  "token_cost": {
    "total": 0.0,
    "currency": "USD",
    "breakdown": {
      "crawl": 0.0,
      "clean": 0.0,
      "elevate": 0.0,
      "verify": 0.0
    }
  },
  "machine_verified": true,
  "review": {
    "status": "agent_reviewed",
    "reviewer": "pipeline-validate",
    "reviewed_at": "2026-08-20T08:33:14+00:00",
    "comments": "schema 0 error + 溯源一致 + 成本达标"
  },
  "provenance": {
    "extracted_by": "codex",
    "extracted_at": "2026-08-20T04:56:41+00:00",
    "pipeline": "collect_hf_papers.py + build_entries.py v0.2（规则管线）",
    "access_urls": [
      "https://huggingface.co/api/daily_papers?limit=10"
    ],
    "card_generated_at": "2026-08-20T08:33:14+00:00",
    "card_pipeline": "enrich_human_stream.py v0.1（规则模板，零 Token）"
  }
}