Pith Number

pith:HHMTDWQR

pith:2026:HHMTDWQRLTOTLC65GTMEK3JEFW

not attested not anchored not stored refs resolved

Continual Learning with Multilingual Foundation Model

Barathi Ganesh HB, Juuso Eronen, Michal Ptaszynski, Rene Melendez

Language-specific decision thresholds improve F1 scores by 2-5 percent in multilingual reclaimed slur detection without retraining the model.

arxiv:2605.13415 v1 · 2026-05-13 · cs.CL · cs.AI · cs.LG

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\pithnumber{HHMTDWQRLTOTLC65GTMEK3JEFW}

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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

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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

The threshold-based optimization yields 2-5% absolute F1 improvement without requiring model retraining.

C2weakest assumption

That the back-translation via GPT-4o-mini accurately preserves the semantic content and class distribution ratios for the slur reclamation task.

C3one line summary

Framework using XLM-RoBERTa, back-translation augmentation, and language-specific thresholds detects reclaimed slurs with 2-5% F1 score gains.

References

19 extracted · 19 resolved · 2 Pith anchors

[1] E. Zsisku, A. Zubiaga, H. Dubossarsky, Hate speech detection and reclaimed language: Mitigating false positives and compounded discrimination, in: Proceedings of the 16th ACM Web Science Conference, 2 2024

[2] B. R. Chakravarthi, R. Priyadharshini, T. Durairaj, J. P. McCrae, P. Buitelaar, P. Kumaresan, R. Pon- nusamy, Overview of the shared task on homophobia and transphobia detection in social media commen 2022

[3] Popa-Wyatt, Reclamation: Taking back control of words, Grazer Philosophische Studien 97 (2020) 159–176 2020

[4] C. Ferrando, L. Draetta, M. Madeddu, M. Sosto, V. Patti, P. Rosso, C. Bosco, J. Mata, E. Gualda, Multipride at evalita 2026: Overview of the multilingual automatic detection of slur reclamation in the 2026

[5] R. J. Tallarida, R. B. Murray, Chi-square test, in: Manual of pharmacologic calculations: with computer programs, Springer, 1987, pp. 140–142 1987

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T02:44:47.378866Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

39d931da115cdd358bdd34d8456d242db5366391b30e953d0905495937051540

Aliases

arxiv: 2605.13415 · arxiv_version: 2605.13415v1 · doi: 10.48550/arxiv.2605.13415 · pith_short_12: HHMTDWQRLTOT · pith_short_16: HHMTDWQRLTOTLC65 · pith_short_8: HHMTDWQR

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/HHMTDWQRLTOTLC65GTMEK3JEFW \
  | 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: 39d931da115cdd358bdd34d8456d242db5366391b30e953d0905495937051540

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "161366b1306ea51d6595ed2670b6267ec1c7f470f116c3f93c06224b2e3633b8",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-05-13T12:10:47Z",
    "title_canon_sha256": "7fef85e0136a36369f84f235c263059e5a84b68c854ae954a9d5d593b0566bf7"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13415",
    "kind": "arxiv",
    "version": 1
  }
}