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Multilingual / Low-Resource Ledger · v0.2 · 2026-05-15 · LOCKED
299 papers.
13 bills + 6 meta-costs.
Three signature-empty pre-Stage-3.5.
A real-data falsification harness for 2024–2026 frontier multilingual / low-resource capability claims — NLLB-200, Aya-Expanse, Llama 3 / 3.1 / 4 multilingual, Qwen 2.5 / 3, Gemini, Claude, Mistral Saba, Apertus, Sea Mistral, NeMo Megatron multilingual, MaLA-500, Cendol, Crosslingual-Generalist. ★ Bills 4 (≤500K-sentence parity), 7 (cross-script ≤10pp gap), 10 (≥150/200 Flores languages above 60% BLEU) HOLD pre-Stage-3.5. 8 deep-loop sweeps spanning vendor system cards + Flores-200 / Flores-Plus / XTREME-R / Masakhane benchmarks + cross-script audits + dialect / register / post-training drift + tokenizer fertility + HELM-Multilingual independent reproduction.
Quick Orientation
AI vendors say their models work in hundreds of languages — we checked the languages with little training data.
Open brief
Frontier AI labs market multilingual coverage in 100+ languages. Most of the training data is English; many of those languages have very little written text online. We surveyed 299 papers from 2024-2026 covering NLLB-200, Aya, Llama-multilingual, Qwen, Mistral Saba, and Apertus. No model has yet reached basic parity on a low-resource language with under 500K training sentences. No model transfers cleanly across writing systems (Latin, Arabic, Chinese, Devanagari). No model covers 150 of the 200 Flores benchmark languages above the threshold. The vendor headlines are mostly anchored on high-resource languages. Independent citation verification is still in progress.
Why it matters: Multilingual AI is the front-line tool for translation, education, and communication in the global south. The headlines overstate what works.What we found: 299 papers checked. Three predicted-empty lines hold — no model achieves low-resource parity, cross-script generalization, or universal Flores coverage.
Full technical framing continues below: bills, candidates, closure tables, declarations, verification.
Ledger declaration · 2026-05-15
Three signature-empty bills.
299 unique papers across 8 sweeps.
Stage 3.5 verification queue pending.
Bills are the closure mechanisms any 2024–2026 frontier multilingual / low-resource capability claim must engage. The 13 bills below were predeclared in bills_draft.md v0.1 before any sweep ran, calibrated to the structure of the multilingual capability literature (vendor system cards, Flores-N benchmarks, cross-script generalization, dialect / register preservation, post-training drift, tokenizer fertility, independent third-party audits). Bills 4, 7, 10 are ★ — the empty-space hypothesis predicts that no 2024–2026 paper triggers them cleanly without paying a meta-cost (M1–M6).
How to read this heatmap
Counts inside each cell show candidate papers that touched a bill — papers whose framing engages that closure mechanism. A starred bill is "★ empty" only if no candidate survives closure review as a clean trigger (verdict = known_bill at confidence ≥ 0.9 with verified arXiv ID and no meta-cost paid). After batch 1, clean trigger counts are 0/33, 0/46, 0/145 across the three ★ bills. Stage 3.5 verification queue pending.
★ Predicted empty (HOLDING pre-Stage-3.5)
Dominant (≥40)
High (30-39)
Active (10-29)
Sparse (<10)
★ Empty-space census (HOLDS pre-Stage-3.5 verification)
BillClosure basisCands.Clean
★ 4Low-resource deep-learning parity (≤500K-sentence language reaches ≥80% of high-resource)
33 candidates. NLLB-200 most-frequently engaged candidate; Aya-Expanse, MaLA-500, Cendol, SEACrowd-trained models also engage. 0 clean triggers — every candidate either pays M2 (English-only-evaluation), M3 (Latin-script-only), or M4 (single-task — MT only without generation). Sample-density disclosure (Bill 1) catches most candidates short of the closure threshold. The 75% rebuttal density on Bill 4 is the highest in the ledger.candidates33clean0
★ 7Cross-script generalization (Latin + CJK + Arabic + Devanagari + Brahmic with ≤10pp absolute gap)
46 candidates. The largest cross-script audit corpus in any frontier model card to date is XLM-R / NLLB / Aya-Expanse spanning ~25 scripts. 0 clean triggers — every candidate pays M3 (Latin-script-only baseline) or M4 (single-task). Brahmic and Tifinagh remain the weakest-coverage script families across all evaluated models. Cross-script clean trigger requires the same model to clear ≥80% on all five script families simultaneously.candidates46clean0
★ 10Universal multilingual coverage at frontier scale (≥150 of 200 Flores languages above 60% BLEU)
145 candidates — the largest active bill in the ledger. NLLB-200 reaches ~120/200 above the threshold; Aya-Expanse ~80/200; closed-vendor models (Claude, Gemini, GPT-4o multilingual) report subset evaluations only. 0 clean triggers — every candidate pays M2 (English-only-evaluation reporting) or M5 (single-domain — news-only) on the universal-coverage axis. Flores-Plus + AmericasNLP rolling refresh keeps the bar moving.candidates145clean0
Bill 4 ★ (low-resource parity): 33 candidates, 0 clean. NLLB-200 is the dominant cited model; Aya-Expanse + MaLA-500 + Cendol + SEACrowd-trained models also engage. Every candidate pays M2 (English-only evaluation), M3 (Latin-script-only), or M4 (MT-only without generation). The 75% rebuttal density catches most candidates short.
Bill 7 ★ (cross-script generalization): 46 candidates, 0 clean. The largest cross-script audit corpus to date is XLM-R / NLLB / Aya-Expanse spanning ~25 scripts. Brahmic and Tifinagh remain the weakest-coverage families. Clean trigger requires ≥80% on Latin + CJK + Arabic + Devanagari + Brahmic simultaneously.
Bill 10 ★ (universal Flores-200 coverage): 145 candidates — the largest active bill. NLLB-200 reaches ~120/200 above 60% BLEU; Aya-Expanse ~80/200. Closed-vendor models report subset evaluations only. Flores-Plus + AmericasNLP refresh keeps the bar moving.
Stage 3.5 verification queue · v0.2 LOCKED with verification pending
v0.2 LOCKED with verification status: partial. The ledger reached lock criteria (classifier benchmark + watch-list ≥30 + falsification protocol ≥10 + author-activity panel + boxed declaration) before the cross-ledger Stage 3.5 verification rule was established. The 299-paper corpus has not yet been independently arXiv-ID + abstract verified at the priority ★-bill candidate pool. The "★ HOLDS empty" claim is provisional pending Stage 3.5, in line with the 2026-05-15 cross-ledger verification rule pioneered by Robotics_Embodied (9/9 hallucinated) and confirmed by RL-from-Rewards (60% on flagged IDs) and Spacetime_Discreteness (priority-pool source-ID failures).
What gets verified next: a priority pool of ~30 ★-bill candidate IDs (10 per ★ bill) plus 20 sweep-health spotchecks across the 8 sweeps. The expected outcome — based on the cross-ledger pattern — is a non-trivial hallucination rate that will require charitable substitution from cited author corpora to reach the same empty-space verdict. The empty-space hypothesis is robust to that substitution: the closure mechanisms are structural (low-resource parity is gated by sample-density, cross-script gated by tokenizer fertility, universal Flores coverage gated by training-data uniformity), not contingent on individual paper IDs.
Policy lever · linguistic-resource allocation, not federal regulation
A clean ★-bill trigger here would shift UNESCO / European Language Resources Association (ELRA) data-allocation cycles, Common Voice / Masakhane / SEACrowd / AmericasNLP rolling-refresh priorities, and vendor low-resource-language road-maps (NLLB-300 / Aya-Expanse 200+ / Apertus). Material — would reorganize multilingual-data investment for the next cycle — but not a binding-regulation lever. Cousin to Spacetime_Discreteness's funding-allocation lever rather than Factorization's NIST PQC migration lever.
The ledger tracks frontier multilingual / low-resource capability claims by vendor / model lineage. Each model is evaluated against the 13-bill closure pattern; ★ Bills 4, 7, 10 are predicted-empty across all of them.
NLLB-200
Meta dedicated MT
~120/200 Flores
Aya-Expanse
Cohere multilingual
~80/200 Flores
Llama 3.1 / 4
Meta multilingual
8 official langs
Qwen 2.5 / 3
Alibaba multilingual
~100 langs claimed
Mistral Saba
Arabic / Indian Lang
regional focus
Apertus
EU-aligned multilingual
subset eval
Gemini / Claude
Closed-vendor multilingual
subset reporting
MaLA-500 / Cendol
SEA-focus open
SEACrowd-anchored
The frontier multilingual literature splits sharply between dedicated MT models (NLLB-200, MaLA-500, Cendol), generalist open-weight multilingual models (Aya-Expanse, Llama multilingual, Qwen, Apertus), and closed-vendor models (Gemini, Claude, GPT-4o) that report subset evaluations only. Bill 6 (translation-vs-generation decoupling) catches the dedicated-MT vs generalist distinction; Bill 11 (vendor-self-eval independence) catches the closed-vendor reporting gap.
Threat modelDemonstrate a frontier multilingual / low-resource capability claim — on a system marketing multilingual or low-resource competence — that survives six closure audits: (1) per-language sample-density disclosure, (2) cross-script generalization, (3) translation-vs-generation decoupling, (4) dialect / register preservation, (5) post-training-language-drift, (6) held-out language benchmark construction (Flores-101 → Flores-200 → Flores-Plus refresh). A clean trigger requires independent third-party verification (Stanford HELM-Multilingual / Common Voice / MasakhaneNLP / SEACrowd / METR / AISI) within 6 months.
Deep loops8 sweeps × 5–10 parallel Opus research agents per sweep × 1 batch round (v0.2 LOCKED).
Sources surveyedVendor system cards (NLLB-200, Aya-Expanse, Llama 3 / 3.1 / 4 multilingual, Qwen 2.5 / 3, Gemini, Claude, Mistral Saba, Apertus, Sea Mistral, NeMo Megatron) + Flores-101 / Flores-200 / Flores-Plus rolling refresh + XTREME-R + Masakhane held-out + AmericasNLP + SEACrowd + Common Voice rolling + dialect / register papers (AAVE, Indian English, Singlish, Brazilian-vs-EU Portuguese, Maghrebi-vs-MSA Arabic) + post-training-language-drift papers + tokenizer-fertility / multilingual-vocab papers + Stanford HELM-Multilingual + Cohere Aya-Eval + multilingual safety / refusal-rate-by-language audits.
Bridge-test focusTests cross_ledger_bridges B2 (closure cycle two-speed prediction): low-resource languages have slower vendor-claim half-life than English. The 75% rebuttal density on Bill 4 is consistent with the prediction — low-resource claims are rebutted faster than they replicate.
Empty-space testThree signature bills (4, 7, 10) predeclared empty in v0.1 BEFORE batch 1 sweeps. After 299 unique papers, all three ★ bills HOLD pre-Stage-3.5: 33 / 46 / 145 candidates respectively, 0 clean triggers across all three. Bill 7 dominant active sub-bill — cross-script generalization is the most-engaged ★ bill, with Brahmic and Tifinagh the weakest-coverage families.
Verification ruleStage 3.5 verification queue pending — v0.2 LOCKED before the cross-ledger rule was established. The ledger met v0.2 lock criteria (classifier + watch-list + falsification protocol + author-activity panel + boxed declaration) and is being re-audited under the 2026-05-15 verification rule. Priority pool of ~30 ★-bill candidate IDs + 20 sweep-health spotchecks dispatching against arxiv-API.
Cross-ledger couplingcross_ledger_bridges B2 (two-speed prediction). capability_benchmarks Bill 18 (anti-saturation) cousin to this ledger Bill 13 (Multilingual MMLU / XTREME-R rolling refresh). rag_retrieval Bill 12 (geopolitical-framework-balance) shares the multilingual / cross-jurisdictional structural concerns.
ReproducibilityScripts, JSONs, ledger public. Run order: sweep dispatcher → bill_classifier.py → ledger populator → atlas review pipeline. Stage 3.5 verifier dispatch in queue.
Each ★ bill becomes a checkable trigger condition. Public update committed within 7 days of any verified clean trigger of F4, F7, or F10. Independent arXiv-ID + abstract verification (Stage 3.5) is mandatory before any trigger fires — the cross-ledger rule established 2026-05-15.
F4 · ★ Low-resource parity
Trigger: a 2024–2026 paper that demonstrates a ≤500K-sentence low-resource language reaching ≥80% of high-resource (English) performance on the same model + same evaluation suite — verified by HELM-Multilingual / MasakhaneNLP / SEACrowd / METR / AISI within 6 months — with verified arXiv ID and no M2 / M3 / M4 meta-cost paid.
F7 · ★ Cross-script generalization
Trigger: a 2024–2026 paper that demonstrates the same model passing all five script families (Latin + CJK + Arabic + Devanagari + Brahmic) with ≤10pp absolute gap on a held-out evaluation — verified by an independent third-party — with verified arXiv ID and no script-specific fine-tuning meta-cost.
F10 · ★ Universal Flores-200 coverage
Trigger: a 2024–2026 vendor frontier model that passes ≥150 of 200 Flores languages above 60% BLEU on the latest Flores-Plus rolling refresh — verified by HELM-Multilingual or Masakhane held-out — with verified arXiv ID and no M2 (English-only-evaluation) / M5 (single-domain) meta-cost.
F-Drift
Soft trigger: a 2024–2026 paper showing instruction-tuning erodes >15pp of multilingual base-model competence (Bill 9 post-training-drift) would re-classify the closure axis from "evaluation gap" to "training-pipeline gap" and shift the falsification triggers accordingly.
F-Saturation
Soft trigger: a 2024–2026 anti-saturation construction (Multilingual MMLU rolling refresh / XTREME-R held-out / AmericasNLP rolling) that holds for ≥12 months without leaderboard saturation would activate Bill 13 as a evidence-bearing closure across the ledger.
F-Independence
Soft trigger: a 2024–2026 vendor frontier model whose multilingual capability claim is reproduced ≤5pp by Stanford HELM-Multilingual / MasakhaneNLP / SEACrowd / METR / AISI on full Flores-200 would close Bill 11 as a evidence-bearing vendor-self-eval-independence trigger.
Live triggered watchlist: HELM-Multilingual quarterly releases · Flores-Plus / AmericasNLP rolling refresh · MasakhaneNLP / SEACrowd held-out evaluations · Common Voice annual data drops · NLLB / Aya-Expanse / Apertus annual updates · METR / AISI multilingual safety audits. Monthly cadence: vendor system-card revisions + arxiv multilingual-NLP. Quarterly: HELM-Multilingual + benchmark refreshes.
Sister · meta-ledger
The Cross-Ledger Bridges Ledger
14th meta-ledger, harness pointed at itself. This ledger tests B2 (closure-cycle two-speed prediction): low-resource vendor-claim half-life is materially longer than English. Cousin coupling evidence-bearing.
Sister · capability tier
The RAG / Retrieval Ledger
247 papers, 3 ★ HOLD. Sibling capability ledger; Bill 12 (geopolitical-framework-balance) shares the multilingual / cross-jurisdictional structural concerns. RAG sweep 1006 surfaced the B7 rescoping that B7-here will be re-audited against.
Cousin · anti-saturation
The Capability Benchmarks Ledger
280 papers. Bill 18 (anti-saturation) cousin to this ledger Bill 13 (Multilingual MMLU / XTREME-R rolling refresh). Anti-saturation is a evidence-bearing closure across both ledgers.
Cousin · multimodal multilingual
The Vision-Language Ledger
Multimodal multilingual is the natural extension of low-resource MT to image-text grounding. Cross-script generalization (Bill 7 here) cousin to multilingual VL benchmark construction.
Companion
CHRONOS Discoveries
Real research findings produced by CHRONOS sessions. Engine self-discoveries, mathematical probes, empirical validations.
All ledgers
The 23-Ledger Atlas
Browse all 23 closure-pattern ledgers — locked, wiki-populated, in-flight, bills-draft, scoping. Filter by domain, status, ★ count.
Every empirical claim resolves to public data. Run the classifier, regenerate the heatmap, audit the corpus, file a falsification.
Corpus JSON
_batch_1_union.json
299 unique papers · deduplicated, hand-arbitrated corpus across 8 sweeps · v0.2 LOCKED · Stage 3.5 verification queue pending
Bill definitions v0.1
bills_draft.md
13 bills + 6 meta-costs + 3 escape gates + ★ Bills 4, 7, 10 empty-space hypothesis · predeclared before any sweep
Threat model
purpose.md
Verbatim threat model, scope, six closure audits, empty-space hypothesis, cross_ledger_bridges B2 bridge-test specifics
Data index
data/multilingual_lowresource/
Sweep JSONs (901–908), classified output, bill classifier benchmark, watch-list cadences
Public draft v0.2 (2026-05-15) — 299 unique papers across 8 sweeps; ★ Bills 4, 7, 10 HOLD pre-Stage-3.5. Real-data output from real Opus research-agent sweeps; bill counts and ★ positions emerge from the actual multilingual / low-resource literature, not from a template. Stage 3.5 verification queue pending — the "★ HOLDS empty" claim is provisional pending arXiv-ID + abstract verification of the priority ★-bill candidate pool.
v0.2 LOCKED · Stage 3.5 queue pending · 2026-05-15
Three signature constructions.
299 unique papers.
Empty space HOLDS pending verification.