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pith:CRLXGX6H

pith:2023:CRLXGX6HLNAR5TGXA74634JOUB
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ChemCrow: Augmenting large-language models with chemistry tools

Andres M Bran, Andrew D White, Carlo Baldassari, Oliver Schilter, Philippe Schwaller, Sam Cox

An LLM agent augmented with 18 chemistry tools autonomously plans and executes real syntheses.

arxiv:2304.05376 v5 · 2023-04-11 · physics.chem-ph · stat.ML

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Claims

C1strongest claim

Our agent autonomously planned and executed the syntheses of an insect repellent, three organocatalysts, and guided the discovery of a novel chromophore. Our evaluation, including both LLM and expert assessments, demonstrates ChemCrow's effectiveness in automating a diverse set of chemical tasks.

C2weakest assumption

That the base large language model can reliably interpret tool outputs, avoid hallucinated chemistry, and produce valid multi-step plans without human correction or post-hoc filtering.

C3one line summary

ChemCrow augments LLMs with 18 expert chemistry tools to autonomously plan and execute syntheses and guide molecular discoveries in organic synthesis, drug discovery, and materials design.

References

118 extracted · 118 resolved · 13 Pith anchors

[1] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 2018 · arXiv:1810.04805
[2] D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A., et al 2020
[3] On the Opportunities and Risks of Foundation Models 2021 · arXiv:2108.07258
[4] PaLM: Scaling Language Modeling with Pathways 2022 · arXiv:2204.02311
[5] Sparks of Artificial General Intelligence: Early experiments with GPT-4 2023 · arXiv:2303.12712

Formal links

2 machine-checked theorem links

Cited by

38 papers in Pith

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First computed 2026-05-17T23:38:50.480970Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

1457735fc75b411eccd707f9edf12ea06da375736e27cd84892fb3461752f2e3

Aliases

arxiv: 2304.05376 · arxiv_version: 2304.05376v5 · doi: 10.48550/arxiv.2304.05376 · pith_short_12: CRLXGX6HLNAR · pith_short_16: CRLXGX6HLNAR5TGX · pith_short_8: CRLXGX6H
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CRLXGX6HLNAR5TGXA74634JOUB \
  | 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: 1457735fc75b411eccd707f9edf12ea06da375736e27cd84892fb3461752f2e3
Canonical record JSON
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
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    "submitted_at": "2023-04-11T17:41:13Z",
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