What is recorded here?
EAGLE conditioned feature-level drafts on one-step-advanced tokens; EAGLE2 selected context-dependent draft trees from confidence scores; EAGLE3 removed feature-regression constraints and trained multi-layer-fused token drafts using training-time rollout tests.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
One family with three source-specific deltas, not three inventions of speculative sampling. Losslessness depends on the inherited exact verification/sampling procedure and implementation; reported speedups are model, workload, hardware and batch dependent. EAGLE2 avoids additional training beyond EAGLE, not all draft-model training; EAGLE3 changes and trains the drafter.
Read the original work
- EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
- EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees
- EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Yuhui Li; Fangyun Wei; Chao Zhang; Hongyang Zhang
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
EAGLE family: feature-conditioned and dynamically structured speculative drafts
EAGLE conditioned feature-level drafts on one-step-advanced tokens; EAGLE2 selected context-dependent draft trees from confidence scores; EAGLE3 removed feature-regression constraints and trained multi-layer-fused token drafts using training-time rollout tests.
Scientific scope
One family with three source-specific deltas, not three inventions of speculative sampling. Losslessness depends on the inherited exact verification/sampling procedure and implementation; reported speedups are model, workload, hardware and batch dependent. EAGLE2 avoids additional training beyond EAGLE, not all draft-model training; EAGLE3 changes and trains the drafter.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Yuhui Li; Fangyun Wei; Chao Zhang; Hongyang Zhang
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.