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Paper Citation Record · LEDGER

Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.06954.

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

pith.paper-citation-record.v1
2404.06954 v1

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 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:23:09.584104Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T03:06:30.314947Z

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 3a000fd8-6184-4257-95fa-d42a5754022d · inbound

Distributed Collaborative Inference System in Next-Generation Networks and Communication cites this paper.

Distributed Collaborative Inference System in Next-Generation Networks and Communication Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T19:23:09.584104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:23:09.584104Z digest=sha256:ab4af2cc602b902868188a2d5682dee9abd8f9244b4fa29643d9959a1d6a1b53

Observation b6ae7ff4-8ff5-45ac-9468-cac4efb6cb83 · inbound

AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference cites this paper.

AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T22:18:51.387701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:18:51.387701Z digest=sha256:0584640ca4adad8f22f6510342c59075478c1b430d34f019df95f5b3f92257ea

Observation 4c017860-a3d9-485e-91f7-1e1be7523979 · inbound

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies cites this paper.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:51:52.490908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.490908Z digest=sha256:57d8915e66935318c559b00717b5ebb3ddfae06391d8fa40453f6b19bdf1f0d3

Observation fa3d898d-3dde-4b42-91bb-e09e8818345f · inbound

Experience-Driven Dynamic Exits for LLMs with Reinforcement Learning cites this paper.

Experience-Driven Dynamic Exits for LLMs with Reinforcement Learning Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-02T03:06:30.317060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-28T10:19:02.938980Z digest=sha256:e42a29084fcf033394ca1a414f3811f65c14b6ba6c9ffa1b1dedd88465039a3d

Observation 898e0630-1ef5-4d91-a8e3-2c5f67875d7e · inbound

CausalGate: Causal Importance Distillation for Transformer Module Pruning cites this paper.

CausalGate: Causal Importance Distillation for Transformer Module Pruning Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-01T12:27:54.852003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:27:54.852003Z digest=sha256:f16dd050a46a3150da3e971e05ad1321ae9ac041e15c93d4b0f195b2ce3f3ff9