Pith Number

pith:7SNFBXEI

pith:2024:7SNFBXEIXODAJYKXKQM2UTNL3H

not attested not anchored not stored refs pending

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

Abhimanyu Hans, Aniruddha Saha, Avi Schwarzschild, Hamid Kazemi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Valeriia Cherepanova

arxiv:2401.12070 v3 · 2024-01-22 · cs.CL · cs.AI · cs.LG

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{7SNFBXEIXODAJYKXKQM2UTNL3H}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

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.

Cited by

18 papers in Pith

Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift

CASPER in the Machine: Insights into Character Variety in LLM-Generated Stories

PolyAlign: Conditional Human-Distribution Alignment

DetectZoo: A Unified Toolkit for AI-Generated Content Detection Across Text, Audio, and Image Modalities

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences

Receipt and verification

First computed	2026-07-05T09:19:53.649621Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

fc9a50dc88bb8604e1575419aa4dabd9cb0a40fb9a22c44eeb3d5ec8f5819352

Aliases

arxiv: 2401.12070 · arxiv_version: 2401.12070v3 · doi: 10.48550/arxiv.2401.12070 · pith_short_12: 7SNFBXEIXODA · pith_short_16: 7SNFBXEIXODAJYKX · pith_short_8: 7SNFBXEI

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/7SNFBXEIXODAJYKXKQM2UTNL3H \
  | 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: fc9a50dc88bb8604e1575419aa4dabd9cb0a40fb9a22c44eeb3d5ec8f5819352

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "d552c7d2fa5b027ec26981d3d687b1e1dd619953995f77315913ff406b8d34e8",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.LG"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2024-01-22T16:09:47Z",
    "title_canon_sha256": "fd8652e9396076fef412d58b7febaac05a4f8d366e9a683b5e6c67b9f45194c0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2401.12070",
    "kind": "arxiv",
    "version": 3
  }
}