Pith Number

pith:YDR4FNFU

pith:2026:YDR4FNFU3VBT7K44KZP72C3RY3

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PRIM: Meta-Learned Bayesian Root Cause Analysis

Amadou Ba, Anish Dhir, Bradley Eck, Christopher Lohse, Jonas Wahl, Marco Ruffini

PRIM frames root cause analysis as Bayesian inference over a synthetic prior of causal models to enable fast zero-shot detection of distributional changes.

arxiv:2605.08786 v2 · 2026-05-09 · cs.LG

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\pithnumber{YDR4FNFU3VBT7K44KZP72C3RY3}

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Claims

C1strongest claim

PRIM infers distributional differences without explicit statistical testing, and implicitly learns causal structure without model fitting at test time, enabling zero-shot inference in 17 ms for systems with up to 100 variables.

C2weakest assumption

The synthetic prior of causal models used for meta-training is sufficiently representative of the structural and distributional properties of the target real-world systems (PetShop, CausRCA, and similar domains).

C3one line summary

PRIM is a meta-learned Bayesian RCA method that marginalizes structural uncertainty via a MACE transformer neural process for zero-shot inference on systems up to 100 variables.

References

56 extracted · 56 resolved · 0 Pith anchors

[1] Bruinsma, and Richard E 2024

[2] Causal chain analysis and root causes: the giwa approach 2004

[3] Why did the dis- tribution change? InInternational Conference on Artificial Intelligence and Statistics, pages 1666–1674 2021

[4] Causal structure- based root cause analysis of outliers 2022

[5] Causeinfer: Automatic and distributed performance diagnosis with hierarchical causality graph in large distributed systems 2014

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:00:41.579771Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c0e3c2b4b4dd433fab9c565ffd0b71c6ee2cf78f505bfb7538dba9aee774811a

Aliases

arxiv: 2605.08786 · arxiv_version: 2605.08786v2 · doi: 10.48550/arxiv.2605.08786 · pith_short_12: YDR4FNFU3VBT · pith_short_16: YDR4FNFU3VBT7K44 · pith_short_8: YDR4FNFU

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/YDR4FNFU3VBT7K44KZP72C3RY3 \
  | 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: c0e3c2b4b4dd433fab9c565ffd0b71c6ee2cf78f505bfb7538dba9aee774811a

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "2881d97db176c55651176b3318e1daa4c4f953dea28b5460274bdd5c0ce6b8bf",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-09T08:14:09Z",
    "title_canon_sha256": "aa7eac8c29da22b031aa061f0c79cf3b566c23223ad051f0b6752485dd174d16"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.08786",
    "kind": "arxiv",
    "version": 2
  }
}