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Paper Citation Record · LEDGER

Cascade Speculative Drafting for Even Faster LLM Inference

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2312.11462.

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

pith.paper-citation-record.v1
2312.11462 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T09:35:53.518187Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T23:23:50.781491Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5c67dcdf-0e97-430d-b66c-3414d1333135 · inbound

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

EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty Cascade Speculative Drafting for Even Faster LLM Inference

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:15:49.372771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-15T00:15:49.303458Z digest=sha256:0a0f80cc1181031683f3b840c181331e8f1ca1aac946f2ca12db4c889b9e8507

Observation 2984eb47-39a1-4714-864b-ee6bb00366f2 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models Cascade Speculative Drafting for Even Faster LLM Inference

Reference 245

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T02:39:33.371517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:892ca87cfd9159cfb5960e9ae0b125fbe43facc2d3593d182bee9fd6808f79e2

Observation f2536f8f-5d7d-4163-bbe9-7a879f289637 · inbound

Reasoning Can Be Restored by Correcting a Few Decision Tokens cites this paper.

Reasoning Can Be Restored by Correcting a Few Decision Tokens Cascade Speculative Drafting for Even Faster LLM Inference

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:57:46.878572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T20:56:48.771058Z digest=sha256:9427ceede483acfae00ccc62f7729202a34e2d0003136307cec4bceb976f8c3b

Observation 9ff69a76-141f-4466-9cd4-d80533d3c6df · inbound

UCCI: Calibrated Uncertainty for Cost-Optimal LLM Cascade Routing cites this paper.

UCCI: Calibrated Uncertainty for Cost-Optimal LLM Cascade Routing Cascade Speculative Drafting for Even Faster LLM Inference

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-20T23:23:50.785877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T23:23:45.561978Z digest=sha256:0e44c7f11f72c7d280bdf22a6242f6f50840049e5869b13e4f57a45e05eb6c1c

Observation c91311fc-c99d-4751-b233-5b0f3821ab70 · inbound

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing cites this paper.

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing Cascade Speculative Drafting for Even Faster LLM Inference

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T09:35:53.518187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T09:35:53.518187Z digest=sha256:0e4f850dbd6dfe63acfd68718b8e9cabefd435a8b1c4f70ed2c1720d636c88ba