Pith Number

pith:L7D72N3N

pith:2026:L7D72N3NLDDETL3LVORIJACM4X

not attested not anchored not stored refs resolved

CausalReasoningBenchmark: A Real-World Benchmark for Disentangled Evaluation of Causal Identification and Estimation

Ayush Sawarni, Jiyuan Tan, Vasilis Syrgkanis

A benchmark of 173 real-world queries scores causal identification and numerical estimation separately to diagnose AI failures in causal analysis.

arxiv:2602.20571 v2 · 2026-02-24 · cs.AI

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

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{L7D72N3NLDDETL3LVORIJACM4X}

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.

Claims

C1strongest claim

By scoring these two components separately, our benchmark enables granular diagnosis: it distinguishes failures in causal reasoning from errors in numerical execution.

C2weakest assumption

The ground-truth identification specifications and estimates extracted from the 79 source papers and three textbooks are accurate and complete enough to serve as reliable labels for the 173 queries.

C3one line summary

CausalReasoningBenchmark supplies 173 real-world queries that separately grade causal identification specifications and point estimates to expose distinct failure modes in automated causal systems.

References

95 extracted · 95 resolved · 0 Pith anchors

[1] Incumbency disadvantage under electoral rules with intraparty competition: Evidence from japan.The Journal of Politics, 2015 2015 · doi:10.1086/681718

[2] Technical report: Facilitating the adoption of causal inference methods through LLM-empowered co-pilot.arXiv preprint arXiv:2508.10581, 2025 2025 · doi:10.48550/arxiv.2508.10581

[3] How does armed conflict shape investment? evidence from the mining sector.The Journal of Politics, 2022 2022 · doi:10.1086/715255

[4] Taylor C. Boas, F. Daniel Hidalgo, and Neal P. Richardson. The spoils of victory: Campaign donations and government contracts in brazil.The Journal of Politics, 2014. doi: 10.1017/s002238161300145x. U 2014 · doi:10.1017/s002238161300145x

[5] Broockman and Timothy J 2015 · doi:10.1111/ajps.12228

Receipt and verification

First computed	2026-05-17T23:39:04.417543Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

5fc7fd376d58c649af6baba284804ce5c590df7186c0712f5c400bd04a096d4d

Aliases

arxiv: 2602.20571 · arxiv_version: 2602.20571v2 · doi: 10.48550/arxiv.2602.20571 · pith_short_12: L7D72N3NLDDE · pith_short_16: L7D72N3NLDDETL3L · pith_short_8: L7D72N3N

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/L7D72N3NLDDETL3LVORIJACM4X \
  | 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: 5fc7fd376d58c649af6baba284804ce5c590df7186c0712f5c400bd04a096d4d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e2d6378955fdea69a379f372eb8c84bb114ae5363eba723996a3bf3aa595d9e5",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-02-24T05:44:25Z",
    "title_canon_sha256": "72c206eaa9bfed5145e51a2dc55dcdae3634fd7613d3f706ccd14a368f041f98"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.20571",
    "kind": "arxiv",
    "version": 2
  }
}