pith:NG7FBDOS
TIP: Token Importance in On-Policy Distillation
Informative tokens in on-policy distillation come from high student entropy positions and low-entropy positions with high teacher divergence where the student is overconfident and wrong.
arxiv:2604.14084 v3 · 2026-04-15 · cs.LG · cs.AI
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Claims
informative tokens come from two regions: positions with high student entropy, and positions with low student entropy plus high teacher--student divergence, where the student is overconfident and wrong.
That teacher-student divergence reliably flags cases where the student is factually wrong rather than simply differing in style or valid alternative answers.
In on-policy distillation, tokens with high student entropy or low entropy plus high teacher divergence provide dense corrective signal, allowing effective training on under 20% of tokens across math and planning tasks.
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| First computed | 2026-05-21T01:05:19.098471Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
69be508dd2b8497f430c8520f2953eb838b95aea2f271644dea7ad5cec2258cc
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NG7FBDOSXBEX6QYMQUQPFFJ6XA \
| 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: 69be508dd2b8497f430c8520f2953eb838b95aea2f271644dea7ad5cec2258cc
Canonical record JSON
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