Pith Number

pith:MJFEB2OV

pith:2026:MJFEB2OVNVW5WKSW72VUBJPBDO

not attested not anchored not stored refs resolved

Generative Artificial Intelligence for Literature Reviews

Gerit Wagner, Guy Pare, Julian Prester, Reza Mousavi, Roman Lukyanenko

Generative AI can assist with literature reviews through summarization, question answering, and data extraction while requiring attention to risks.

arxiv:2605.16475 v1 · 2026-05-15 · cs.DL · cs.CL

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\usepackage{pith}
\pithnumber{MJFEB2OVNVW5WKSW72VUBJPBDO}

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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

Generative AI capabilities such as summarization of large text corpora, question-answering, data extraction, and translation carry profound implications for the conduct of literature reviews.

C2weakest assumption

That illustrative prompts and suggested strategies remain methodologically sound when applied by typical users without introducing systematic biases, hallucinations, or incomplete coverage that would invalidate the resulting review.

C3one line summary

Generative AI tools can assist literature reviews via summarization, extraction, and question-answering, with the paper providing prompt examples and balanced discussion of opportunities, risks, and open methodological issues.

References

2 extracted · 2 resolved · 0 Pith anchors

[1] (2024) Unmasking bias in arti ﬁcial intelligence: a systematic review of bias detection and miti- gation strategies in electronic health record-based models 2023 · doi:10.1109/weef-

[2] Systems Analysis and Design: An Object-Oriented Ap- proach with UML 2018 · doi:10.1186/s13643-023-02243-z

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-20T00:02:23.930755Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

624a40e9d56d6ddb2a56feab40a5e11b9e0b60e8fba27666ba41029204833eab

Aliases

arxiv: 2605.16475 · arxiv_version: 2605.16475v1 · doi: 10.48550/arxiv.2605.16475 · pith_short_12: MJFEB2OVNVW5 · pith_short_16: MJFEB2OVNVW5WKSW · pith_short_8: MJFEB2OV

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/MJFEB2OVNVW5WKSW72VUBJPBDO \
  | 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: 624a40e9d56d6ddb2a56feab40a5e11b9e0b60e8fba27666ba41029204833eab

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "de45f858a5e532c87bbaf11b93e757604f24ef6c0f1fb0eb0fb0f68cfa7e71d3",
    "cross_cats_sorted": [
      "cs.CL"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.DL",
    "submitted_at": "2026-05-15T15:42:54Z",
    "title_canon_sha256": "87a1644d66e346875a5cb189bd63dd66dd16e707c8c9e24aae4d74eb479cb24c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16475",
    "kind": "arxiv",
    "version": 1
  }
}