Pith Number

pith:BPCVUG4Y

pith:2023:BPCVUG4YF75TKRQPMT5BNG6XWN

not attested not anchored not stored refs resolved

Mind2Web: Towards a Generalist Agent for the Web

Boshi Wang, Boyuan Zheng, Huan Sun, Samuel Stevens, Shijie Chen, Xiang Deng, Yu Gu, Yu Su

Mind2Web supplies over 2000 real-world tasks on 137 live websites so language models can act as generalist agents that follow instructions across unseen sites and domains.

arxiv:2306.06070 v3 · 2023-06-09 · cs.CL

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\usepackage{pith}
\pithnumber{BPCVUG4YF75TKRQPMT5BNG6XWN}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Mind2Web provides three necessary ingredients for building generalist web agents: diverse domains, websites, and tasks; use of real-world websites instead of simulated ones; and a broad spectrum of user interaction patterns. LLMs with HTML filtering by a small LM achieve decent performance even on unseen websites or domains.

C2weakest assumption

That the crowdsourced action sequences collected from workers accurately capture the steps a typical user would take to complete each open-ended task on live websites, and that the 137 sites sufficiently represent the diversity needed for generalization to arbitrary new sites.

C3one line summary

Mind2Web is the first large-scale dataset of real-world web tasks for developing generalist language-guided agents that complete complex actions on diverse websites.

References

45 extracted · 45 resolved · 13 Pith anchors

[1] Puppeteer headless chrome node.js api. https://github.com/puppeteer/puppeteer, 2021 2021

[2] Do As I Can, Not As I Say: Grounding Language in Robotic Affordances 2022 · doi:10.48550/arxiv.2204.01691

[3] On the Opportunities and Risks of Foundation Models 2021 · arXiv:2108.07258

[4] Language models are few-shot learners 1901

[5] Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, and Bryan A. Plum- mer. A dataset for interactive vision-language navigation with unknown command feasibility. In European Confe 2022

Formal links

2 machine-checked theorem links

Cited by

40 papers in Pith

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Receipt and verification

First computed	2026-05-17T23:38:50.329564Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

0bc55a1b982ffb35460f64fa169bd7b343e8c06c3bf433e0006d6409eb904ae2

Aliases

arxiv: 2306.06070 · arxiv_version: 2306.06070v3 · doi: 10.48550/arxiv.2306.06070 · pith_short_12: BPCVUG4YF75T · pith_short_16: BPCVUG4YF75TKRQP · pith_short_8: BPCVUG4Y

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/BPCVUG4YF75TKRQPMT5BNG6XWN \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 0bc55a1b982ffb35460f64fa169bd7b343e8c06c3bf433e0006d6409eb904ae2

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4904546ccd9001c8e9c284d9a2400549c9fc60089e24477b9071ce804fdf6d7a",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2023-06-09T17:44:31Z",
    "title_canon_sha256": "eff6e31b30051f423c394a542c1f3c9b35a370c8ee9a0b56596318dc1aa40794"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2306.06070",
    "kind": "arxiv",
    "version": 3
  }
}