pith:AHTBYOKF
Consistent Diffusion Language Models
A single consistency objective unifies masked and uniform discrete diffusion while delivering state-of-the-art few-step text generation.
arxiv:2605.00161 v2 · 2026-04-30 · cs.LG
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\pithnumber{AHTBYOKFSJBXGAQCRFP2TP5WZC}
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Claims
CDLM establishes a new state of the art on both conditional and unconditional text-generation, consistently outperforming strong base discrete diffusion models and often even multi-stage distilled baselines across sampling budgets, with the largest gains in the few-step regime.
That the exact posterior bridge serves as the natural discrete substitute for the probability-flow ODE and that enforcing path-invariance in expectation across these bridges produces superior denoisers without introducing new failure modes.
CDLM trains denoisers to be path-invariant across stochastic posterior bridges in discrete diffusion, unifying prior methods and achieving new SOTA few-step text generation performance.
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Receipt and verification
| First computed | 2026-06-02T01:03:47.806481Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
01e61c39459243730202895fa9bfb6c8adba3c2bf35d4b9c6288ede46af66422
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/AHTBYOKFSJBXGAQCRFP2TP5WZC \
| 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: 01e61c39459243730202895fa9bfb6c8adba3c2bf35d4b9c6288ede46af66422
Canonical record JSON
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