Pith Number

pith:ZX4LCNNB

pith:2026:ZX4LCNNBPMM7KTJX5KEVLRLLBD

not attested not anchored not stored refs pending

Ceci n'est pas une explication: Evaluating Explanation Failures as Explainability Pitfalls in Language Learning Systems

Ben Knight, Danielle Carvalho, Isaac Pattis, James Edgell, Wm. Matthew Kennedy

AI explanations in language learning tools often look helpful but contain flaws that can reinforce errors and erode trust.

arxiv:2604.26145 v2 · 2026-04-28 · cs.HC · 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{ZX4LCNNBPMM7KTJX5KEVLRLLBD}

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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

AI-generated explanations that appear helpful on the surface but are fundamentally flawed, increasing the risk of attainment, human-AI interaction, and socioaffective harms.

C2weakest assumption

That the six listed dimensions capture the critical failure modes and that the resulting pitfalls actually produce the claimed harms in real learner interactions.

C3one line summary

AI explanations in language learning often fail across six dimensions like diagnostic accuracy and self-regulation support, creating hidden risks that demand better evaluation frameworks such as L2-Bench.

Receipt and verification

First computed	2026-05-25T02:02:15.860230Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

cdf8b135a17b19f54d37ea8955c56b08e2cc6c52fc25fac564ce38fdb88ba9e2

Aliases

arxiv: 2604.26145 · arxiv_version: 2604.26145v2 · doi: 10.48550/arxiv.2604.26145 · pith_short_12: ZX4LCNNBPMM7 · pith_short_16: ZX4LCNNBPMM7KTJX · pith_short_8: ZX4LCNNB

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/ZX4LCNNBPMM7KTJX5KEVLRLLBD \
  | 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: cdf8b135a17b19f54d37ea8955c56b08e2cc6c52fc25fac564ce38fdb88ba9e2

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "7a82e490e5ec65047113eefab395c41d5d81de227ccad0c8c964e067d90dfe72",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-sa/4.0/",
    "primary_cat": "cs.HC",
    "submitted_at": "2026-04-28T22:05:57Z",
    "title_canon_sha256": "4ba3ad451811049a1eb4384fe644ca2e1dd7df86f1ff4d9cb90bb9ba23c0cf75"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.26145",
    "kind": "arxiv",
    "version": 2
  }
}