Pith Number

pith:HVWCAIRU

pith:2026:HVWCAIRUZAYDQNN3NIZV3IOAF4

not attested not anchored not stored refs resolved

Neurodata Without Boredom: Benchmarking Agentic AI for Data Reuse

Kristin Branson, Ling-Qi Zhang

General-purpose AI coding agents handle isolated steps of neuroscience data reformatting but rarely complete error-free end-to-end pipelines.

arxiv:2605.12808 v2 · 2026-05-12 · cs.LG

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

General-purpose coding agents commonly used by scientists performed well on each sub-task, but rarely strung together a fully error-free end-to-end solution. Agents-as-judges are unreliable at catching errors, especially without ground-truth references.

C2weakest assumption

The eight selected papers and their data formats are representative of the broader challenges in neuroscience data reuse and that success on the decoder-training reformatting task is a good proxy for general data-reuse utility.

C3one line summary

AI agents handle individual data-loading and reformatting steps on neuroscience datasets but rarely complete fully error-free end-to-end pipelines, and AI judges are unreliable without ground-truth references.

References

95 extracted · 95 resolved · 1 Pith anchors

[1] The hippocampus as a predic- tive map 2017

[2] Coarse graining, ﬁxed points, and scaling in a large population of neurons 2019

[3] Space is a latent sequence: A theory of the hippocampus 2024

[4] A uniﬁed, scalable framework for neural population decoding 2023

[5] Foundation model of neural activity predicts response to new stimulus types 2025

Receipt and verification

First computed	2026-05-18T03:09:12.565426Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3d6c202234c8303835bb6a335da1c02f3fb0082b8b6c6b7a08db3585c76cae68

Aliases

arxiv: 2605.12808 · arxiv_version: 2605.12808v2 · doi: 10.48550/arxiv.2605.12808 · pith_short_12: HVWCAIRUZAYD · pith_short_16: HVWCAIRUZAYDQNN3 · pith_short_8: HVWCAIRU

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/HVWCAIRUZAYDQNN3NIZV3IOAF4 \
  | 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: 3d6c202234c8303835bb6a335da1c02f3fb0082b8b6c6b7a08db3585c76cae68

Canonical record JSON

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    "abstract_canon_sha256": "abccb7fa725ac053da51d0a16d27bf3cc9e7833cbcced4422c9e0dc4f4cbdd60",
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-12T23:00:18Z",
    "title_canon_sha256": "c5d9543579932b1d88f6f010e158d39d07b100bb766e683d92f41df5c70eaba1"
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