Paper Citation Record · LEDGER

Not All Layers of LLMs Are Necessary During Inference

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2403.02181.

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

pith.paper-citation-record.v1
2403.02181 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:51.721100Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T12:59:53.065299Z

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 65a5f1c8-cb1f-41ac-8afe-021d6ac540f2 · 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 Not All Layers of LLMs Are Necessary During Inference

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:51:51.721100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06a79309-8851-411c-b92e-49e741f4e1eb · inbound

TRACE for Tracking the Emergence of Semantic Representations in Transformers cites this paper.

TRACE for Tracking the Emergence of Semantic Representations in Transformers Not All Layers of LLMs Are Necessary During Inference

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:42:10.919440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1af3c9ca-d5ba-4759-89d8-a1783b92252d · inbound

BiggerGait: Unlocking Gait Recognition with Layer-wise Representations from Large Vision Models cites this paper.

BiggerGait: Unlocking Gait Recognition with Layer-wise Representations from Large Vision Models Not All Layers of LLMs Are Necessary During Inference

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:48.884963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9883a815-5f21-4f95-a1eb-855dcf203db1 · inbound

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits cites this paper.

Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits Not All Layers of LLMs Are Necessary During Inference

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:16.842408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f806f274-382b-4650-88c7-eb6b5c29eb11 · inbound

DLP: Dynamic Layerwise Pruning in Large Language Models cites this paper.

DLP: Dynamic Layerwise Pruning in Large Language Models Not All Layers of LLMs Are Necessary During Inference

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T13:51:17.229319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 758b547f-5e71-42ed-8775-8fc551ed1a5e · inbound

SkipGPT: Dynamic Layer Pruning Reinvented with Token Awareness and Module Decoupling cites this paper.

SkipGPT: Dynamic Layer Pruning Reinvented with Token Awareness and Module Decoupling Not All Layers of LLMs Are Necessary During Inference

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T10:51:51.474200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea168e31-aac8-45c6-9ada-e8dd34e8e2af · inbound

Learning to Skip the Middle Layers of Transformers cites this paper.

Learning to Skip the Middle Layers of Transformers Not All Layers of LLMs Are Necessary During Inference

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T22:40:53.825000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c52b842-cf4b-45e7-8193-9c8129f8ed96 · inbound

The Generalization Ridge: Information Flow in Natural Language Generation cites this paper.

The Generalization Ridge: Information Flow in Natural Language Generation Not All Layers of LLMs Are Necessary During Inference

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T05:32:05.666881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation efce8ef1-28f1-416c-b1fe-982961308b2c · inbound

PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning cites this paper.

PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning Not All Layers of LLMs Are Necessary During Inference

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:59.698293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc2b33b2-b2ca-4e61-ad20-7f2e725eeba2 · inbound

SpecEyes: Accelerating Agentic Multimodal LLMs via Speculative Perception and Planning cites this paper.

SpecEyes: Accelerating Agentic Multimodal LLMs via Speculative Perception and Planning Not All Layers of LLMs Are Necessary During Inference

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-13T19:34:58.789459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3022ec2-1dec-4774-86cc-f6a000948b01 · inbound

ART: Attention Replacement Technique to Improve Factuality in LLMs cites this paper.

ART: Attention Replacement Technique to Improve Factuality in LLMs Not All Layers of LLMs Are Necessary During Inference

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:30:50.936267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 98f661ad-d752-4acd-b51e-5aba33f1dca8 · inbound

Two-dimensional early exit optimisation of LLM inference cites this paper.

Two-dimensional early exit optimisation of LLM inference Not All Layers of LLMs Are Necessary During Inference

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:59:34.249383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c809a79f-d64b-4827-96d9-10c3cbd014b6 · inbound

FASER: Fine-Grained Phase Management for Speculative Decoding in Dynamic LLM Serving cites this paper.

FASER: Fine-Grained Phase Management for Speculative Decoding in Dynamic LLM Serving Not All Layers of LLMs Are Necessary During Inference

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-09T22:59:17.732430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4d52b39b-3349-45cc-b7bc-24048a299838 · inbound

Uncovering the Latent Potential of Deep Intermediate Representations cites this paper.

Uncovering the Latent Potential of Deep Intermediate Representations Not All Layers of LLMs Are Necessary During Inference

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:36:39.238068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 580f8cd7-5742-4426-907a-3b50a66e464c · inbound

Tracing Computation Density in LLMs cites this paper.

Tracing Computation Density in LLMs Not All Layers of LLMs Are Necessary During Inference

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T18:23:50.641403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0172b41d-5f07-47d1-98bc-ea5c03dfda5f · inbound

BMCR: Adaptive Backbone Module Composition via Reinforcement Learning for Remote Sensing Object Detection cites this paper.

BMCR: Adaptive Backbone Module Composition via Reinforcement Learning for Remote Sensing Object Detection Not All Layers of LLMs Are Necessary During Inference

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:46:56.207806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 45e80d92-669e-4507-b095-7fb32045213b · inbound

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering cites this paper.

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering Not All Layers of LLMs Are Necessary During Inference

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-02T17:17:15.073583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1ecd1bd1-d70a-4a0d-ab9f-b80bb7f08137 · inbound

Discovering Millions of Interpretable Features with Sparse Autoencoders cites this paper.

Discovering Millions of Interpretable Features with Sparse Autoencoders Not All Layers of LLMs Are Necessary During Inference

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:59:53.066618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3abb809e-ae2c-4581-b83b-b07fd8c08c75 · inbound

End-to-End Dynamic Sparsity for Resource-Adaptive LLM Inference cites this paper.

End-to-End Dynamic Sparsity for Resource-Adaptive LLM Inference Not All Layers of LLMs Are Necessary During Inference

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-01T17:35:52.028452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a491cf3-9029-4d8c-8950-f06722cc2fed · inbound

The Hard Decision Layer: Evidence for Committed Inference in Transformers cites this paper.

The Hard Decision Layer: Evidence for Committed Inference in Transformers Not All Layers of LLMs Are Necessary During Inference

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T13:18:20.471944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.