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Paper Citation Record · LEDGER

FastDraft: How to Train Your Draft

As of 14 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 3 inbound Pith citation observations for arXiv:2411.11055.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.11055 v3

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:05:26.245187Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:11:55.492311Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-28T19:02:34.511475Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved40
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7168b4f0-36db-486c-8ad3-7741b909ed88 · outbound

This paper cites online" 'onlinestring :=.

FastDraft: How to Train Your Draft online" 'onlinestring :=

Reference 1

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Observation 701e3b89-e2ea-460f-9db5-5d8ad3305628 · outbound

This paper cites write newline.

FastDraft: How to Train Your Draft write newline

Reference 2

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source=arxiv_source observed=2026-08-12T19:05:25.895672Z digest=sha256:ffbb61ae8be2e57b5e9930fb64887fe41694c8dfc133f87da8e3e4e7839d7478

Observation 441a63b7-d75b-4086-8af3-953765ea5e27 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

FastDraft: How to Train Your Draft Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 3

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Observation a007a312-c2e9-4a60-99c1-bf02503eed86 · outbound

This paper cites GPT-4 Technical Report.

FastDraft: How to Train Your Draft GPT-4 Technical Report

Reference 4

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Observation 064f7e30-4dda-4dd2-9c95-7244b2868cbc · outbound

This paper cites To Code, or Not To Code? Exploring Impact of Code in Pre-training.

FastDraft: How to Train Your Draft To Code, or Not To Code? Exploring Impact of Code in Pre-training

Reference 5

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Observation 440d5c34-ceb5-4e07-9ab9-5f56833b9feb · outbound

This paper cites Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

FastDraft: How to Train Your Draft Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Reference 6

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Observation 519d5449-9faf-4202-b1ad-1f15fd91c4e9 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

FastDraft: How to Train Your Draft Evaluating Large Language Models Trained on Code

Reference 7

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Observation a6e5a1e9-63aa-4142-8490-bbb910c71888 · outbound

This paper cites Cascade Speculative Drafting for Even Faster LLM Inference.

FastDraft: How to Train Your Draft Cascade Speculative Drafting for Even Faster LLM Inference

Reference 8

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Observation f192362c-3761-4051-b59d-ca862e4f038d · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 9

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Observation f19460bb-6849-400f-b73f-7c235209a72f · outbound

This paper cites Common crawl.

FastDraft: How to Train Your Draft Common crawl

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8da4a687-87e9-41b4-b90f-c67e9c00a546 · outbound

This paper cites The Llama 3 Herd of Models.

FastDraft: How to Train Your Draft The Llama 3 Herd of Models

Reference 11

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Observation 741f509a-6bb0-4612-b18e-7e4b0d4cf339 · outbound

This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.

FastDraft: How to Train Your Draft TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Reference 12

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Observation 09be8757-4877-46f6-ba46-27d2b4f0e75a · outbound

This paper cites Mask-Predict: Parallel Decoding of Conditional Masked Language Models.

FastDraft: How to Train Your Draft Mask-Predict: Parallel Decoding of Conditional Masked Language Models

Reference 13

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Observation ae1f49ac-f58e-45bb-87ee-b59a2e20a99b · outbound

This paper cites Direct Alignment of Draft Model for Speculative Decoding with Chat-Fine-Tuned LLMs.

FastDraft: How to Train Your Draft Direct Alignment of Draft Model for Speculative Decoding with Chat-Fine-Tuned LLMs

Reference 14

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Observation 0caea0b5-bfcc-4be3-ac07-4952a765646c · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation dd9e81ad-faa8-488d-a287-39a105448c54 · outbound

This paper cites Teaching Machines to Read and Comprehend.

FastDraft: How to Train Your Draft Teaching Machines to Read and Comprehend

Reference 16

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Observation 4f7774a8-dc8e-4587-a6c1-aed28ddd24d6 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

FastDraft: How to Train Your Draft Distilling the Knowledge in a Neural Network

Reference 17

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Observation 7750ef1c-2997-4f75-9610-4f2e2d6c03e0 · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 548c2d62-3d0e-4241-b98d-476ff236e37e · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a9c16394-6265-44da-b528-d623565c8f89 · outbound

This paper cites Scaling Laws for Neural Language Models.

FastDraft: How to Train Your Draft Scaling Laws for Neural Language Models

Reference 20

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Observation cbf9a263-91e5-4b68-be49-f12fd8efee9e · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 21

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Observation 16fe260b-e96b-45ec-acce-fa094c9f6323 · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 22

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Observation 362e6bce-c383-4793-a525-b8e4626f4943 · outbound

This paper cites EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty.

FastDraft: How to Train Your Draft EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty

Reference 23

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Observation 66feeb49-d6f9-442c-bcba-374da4472a58 · outbound

This paper cites EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test.

FastDraft: How to Train Your Draft EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test

Reference 24

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Observation 5f5a9acf-8997-4de7-91d5-b08600951538 · outbound

This paper cites A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity.

FastDraft: How to Train Your Draft A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity

Reference 25

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Observation 193e2be1-49b8-4a45-90f9-4c982a49c87a · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

FastDraft: How to Train Your Draft StarCoder 2 and The Stack v2: The Next Generation

Reference 26

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Observation 14737719-73bc-4267-b544-7915b2d90d20 · outbound

This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.

FastDraft: How to Train Your Draft WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 27

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Observation c9ea1a8e-f15d-4bc0-8023-fbdce99a1b69 · outbound

This paper cites SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification.

FastDraft: How to Train Your Draft SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification

Reference 28

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Observation 23a6f594-5c3d-479d-a8c6-9dd4b75e1002 · outbound

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FastDraft: How to Train Your Draft Cohen, and Mirella Lapata

Reference 29

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verified exact
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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b101aacb-f121-4be3-ab57-48aa3d9ef9d9 · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

FastDraft: How to Train Your Draft The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 30

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Observation bb75272b-3be8-4e92-aad5-fb53d9f98d9c · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0180abb7-e4e3-4bfa-a5a0-0122fbd51f6f · outbound

This paper cites Salesforce wikitext dataset.

FastDraft: How to Train Your Draft Salesforce wikitext dataset

Reference 32

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 22228932-44be-4ceb-a690-b6065fbd49fb · outbound

This paper cites Accelerating Transformer Inference for Translation via Parallel Decoding.

FastDraft: How to Train Your Draft Accelerating Transformer Inference for Translation via Parallel Decoding

Reference 33

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Observation a456d991-f63d-4964-9240-1866850e74b6 · outbound

This paper cites an unresolved cited work.

FastDraft: How to Train Your Draft Unresolved cited work

Reference 34

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Observation b6b6770a-e2b6-49ca-9e93-56745b358c72 · outbound

This paper cites TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding.

FastDraft: How to Train Your Draft TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding

Reference 35

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Observation 1278bfd6-73d5-40ee-98e4-be74643eda40 · outbound

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FastDraft: How to Train Your Draft Hashimoto

Reference 36

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Observation 8c0b3e7d-d109-47b3-8748-c0435bcab713 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

FastDraft: How to Train Your Draft Gemini: A Family of Highly Capable Multimodal Models

Reference 37

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Observation ae9da57c-4fac-4f85-9f21-1339aec6ae1d · outbound

This paper cites SWIFT: On-the-Fly Self-Speculative Decoding for LLM Inference Acceleration.

FastDraft: How to Train Your Draft SWIFT: On-the-Fly Self-Speculative Decoding for LLM Inference Acceleration

Reference 38

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Observation 68826427-75e1-483c-ab9b-8b60b2431d2e · outbound

This paper cites Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing.

FastDraft: How to Train Your Draft Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T19:05:26.222656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 463fc607-a9ab-4ebc-95df-bed53c14024b · outbound

This paper cites Decoding Speculative Decoding.

FastDraft: How to Train Your Draft Decoding Speculative Decoding

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T19:05:26.228466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:05:26.228466Z digest=sha256:490b02c4627760297336cf56f84a84f559de7daadb36420855f1cf3efe445503

Observation 2f37e260-1acc-436e-a116-bca6163f732b · outbound

This paper cites Recurrent Drafter for Fast Speculative Decoding in Large Language Models.

FastDraft: How to Train Your Draft Recurrent Drafter for Fast Speculative Decoding in Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T19:05:26.233764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:05:26.233764Z digest=sha256:eba8ca5698aecff2c3faf82efc9a244e8a1daefea5bbe0bc87dcf822ae97746e

Observation 7d6eb76b-9896-49f6-ae4f-52a110ce636b · outbound

This paper cites Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding.

FastDraft: How to Train Your Draft Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T19:05:26.239816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:05:26.239816Z digest=sha256:a83f89af6ea66aa1c19ce2351fda787a1b1c540cad70eb668487e506a589b663

Observation 1ef0aa40-0f47-4ca8-a18e-1bd8b9d55247 · outbound

This paper cites DistillSpec: Improving Speculative Decoding via Knowledge Distillation.

FastDraft: How to Train Your Draft DistillSpec: Improving Speculative Decoding via Knowledge Distillation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T19:05:26.245187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:05:26.245187Z digest=sha256:d98cf6577d732569fafa9e26348c87ff0135177a1bb6985abe09d5cbcbc2c199

Pith citing papers

Observation 492ec336-ba1b-4506-bf1a-284671b8b310 · inbound

Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies cites this paper.

Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies FastDraft: How to Train Your Draft

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T20:11:55.492311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T20:11:55.492311Z digest=sha256:bb2aba618f85eaa4d2be8a317b112b015ce7b67cf22d4f15abaab91e2af688ef

Observation 3dc36cb5-179e-4667-9a7f-02080105dabb · inbound

Consultant Decoding: Yet Another Synergistic Mechanism cites this paper.

Consultant Decoding: Yet Another Synergistic Mechanism FastDraft: How to Train Your Draft

Reference 36

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unresolved
no resolver link, observed 2026-08-07T11:30:57.380279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:30:57.380279Z digest=sha256:eb79e576bc6ed1af1c44a36888c5f6ddca00daa9222eaef11fc0794bc92fa8ae

Observation d3d37486-874a-4be7-a8a4-b339ccf28817 · inbound

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation cites this paper.

DREAM-S: Speculative Decoding with Searchable Drafting and Target-Aware Refinement for Multimodal Generation FastDraft: How to Train Your Draft

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:02:34.512918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-28T18:55:51.474956Z digest=sha256:28bd060a27351cd046c1ff1db103676c5a559705ebe3570d2874218fb9936682