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Paper Citation Record · LEDGER

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

As of 9 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2505.17420.

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

pith.paper-citation-record.v1
2505.17420 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:53.154620Z

measured 23 of 23 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e01a6648-6985-4ca2-8f98-16d4141d8053 · outbound

This paper cites GPT-4 Technical Report.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.340639Z digest=sha256:a1f5f3c139437c7abdc4b38fd143e174602264e736c88d34cc0b6979c344aa9b

Observation c38aa4c6-73ca-4688-8c6c-c156e5555b90 · outbound

This paper cites an unresolved cited work.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Unresolved cited work

Reference 2

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.362700Z digest=sha256:7582e374425b92ef75171860e915396ace7661bf094e6676a4dd24f4af69c13f

Observation 8d4a2d47-2c56-452f-9eb4-b5de198700b0 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 3

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no resolver link, observed 2026-08-07T14:51:51.422845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.422845Z digest=sha256:8a7f1886ec41dc1078136164591d844669396beb77ece1e2a247d480456ee58b

Observation 76a8c7e2-caa3-4204-8c28-77bb60f2d59f · outbound

This paper cites SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.501090Z digest=sha256:509d4cb35d50486f9c915f45233dc20d5abf2d04e08343a7a4e3615870e00471

Observation 73ed9899-7c75-4117-a10b-8539a60bc3e4 · outbound

This paper cites LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.597620Z digest=sha256:23bdc48603f9ea01b7f09a7cb779cc4117254d32e465a32d9d06c649472196ec

Observation 65a5f1c8-cb1f-41ac-8afe-021d6ac540f2 · outbound

This paper cites Not All Layers of LLMs Are Necessary During Inference.

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.721100Z digest=sha256:272f4814c62ae56adc418ad18c828b2f2bbe78188d4cae9abdcfaef8db35eb1b

Observation d0d265e9-9b28-40c8-9e1e-20c73c06c549 · outbound

This paper cites The Llama 3 Herd of Models.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies The Llama 3 Herd of Models

Reference 7

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source=arxiv_source observed=2026-08-07T14:51:51.855677Z digest=sha256:295f0926bcd593c7d27b39c8aa06bc006b80e82bdc53bf8b835dd24008a92ec9

Observation 73d78bdd-b6f6-4b71-863d-41687c3c861e · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 8

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:51.962063Z digest=sha256:e5e60376317e80868f62665149dd1e7b875427f37e2de2b63f0e5996da3d18d6

Observation fd1e5ce3-886b-4861-9a6d-d54f080ccb42 · outbound

This paper cites an unresolved cited work.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Unresolved cited work

Reference 9

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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.

source=arxiv_source observed=2026-08-07T14:51:52.086524Z digest=sha256:20706f6ffdeb3b07eae005ff0129f076adf0770dfd85dbf5d46295e0c647cc52

Observation 18ed080e-0432-4a98-8c6b-f03e02882084 · outbound

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

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.225072Z digest=sha256:17c206aabdda8af572ae814ac6801ef82b15b25799f4930e9699e1a959854310

Observation 5647efe6-cb62-4864-9568-14b5cf30957d · outbound

This paper cites Measuring Massive Multitask Language Understanding.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Measuring Massive Multitask Language Understanding

Reference 11

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.345584Z digest=sha256:0228b0f1c43e6f06a4109f8b74ee1d603fc19d1dda426ff88592508b360c98ff

Observation df9dcbfb-2cff-4c29-b1ba-04daa3e9a950 · outbound

This paper cites FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping

Reference 12

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no resolver link, observed 2026-08-07T14:51:52.466772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.466772Z digest=sha256:fb4da9e7fe6c8ae573382b0e2f4e873d961e2ae5d80eaa68c170c98ee145dcbc

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

This paper cites Accelerating Inference in Large Language Models with a Unified Layer Skipping Strategy.

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.490908Z digest=sha256:5bbe9544494f5a894b76d2df117dab6f5c8c171b308495fe2927bbf850e6e36e

Observation 16070eb8-038d-4783-9b7f-478af00109b5 · outbound

This paper cites an unresolved cited work.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Unresolved cited work

Reference 14

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raw_fallback, observed 2026-08-07T14:51:53.858909Z

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.

source=arxiv_source observed=2026-08-07T14:51:52.498739Z digest=sha256:227b123e5bf164fd967d44400185bbde8abbd4f37fe1e951d8630121127ea1ab

Observation eb5cbf14-7e40-4a43-b3cd-e3f72118b92b · outbound

This paper cites ShortGPT: Layers in Large Language Models are More Redundant Than You Expect.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies ShortGPT: Layers in Large Language Models are More Redundant Than You Expect

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.519822Z digest=sha256:34e690ca2fbce637ad0413aa97c331b73b5a25ce020454d34fa8c7848dcbd165

Observation 03767f2f-ddb6-4a35-ad71-b4fc76ee627c · outbound

This paper cites Pointer Sentinel Mixture Models.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Pointer Sentinel Mixture Models

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.592199Z digest=sha256:d0230afdec11a1f2d781eabbd90f3301575ad7e788cc985d2deaa2d55f179c09

Observation 39859a22-f103-42b3-83f8-b417879e57a2 · outbound

This paper cites Get To The Point: Summarization with Pointer-Generator Networks.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Get To The Point: Summarization with Pointer-Generator Networks

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.681122Z digest=sha256:81fc23d53c33fd4b9cdc59f7915d92602b6732205b57bb866a59328704b3713d

Observation 1334dc08-0bfb-416d-9eae-d010615e7abb · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 18

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no resolver link, observed 2026-08-07T14:51:52.760222Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.760222Z digest=sha256:73dd35780e423d627657f8c0ffcf6d7a42ba874f162f3ead1498564f187f07f3

Observation aa018563-c17f-483f-9b5a-025aa500af79 · outbound

This paper cites an unresolved cited work.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Unresolved cited work

Reference 19

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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.

source=arxiv_source observed=2026-08-07T14:51:52.857897Z digest=sha256:726828c8b760f65c2ad9839270877e9d31a5ed0c779af0dcd405b63971069145

Observation 39088ef9-e16d-4a31-8e9d-4d56750a9c15 · outbound

This paper cites an unresolved cited work.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Unresolved cited work

Reference 20

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raw_fallback, observed 2026-08-07T14:51:53.478609Z

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.

source=arxiv_source observed=2026-08-07T14:51:52.927099Z digest=sha256:510b94f46e71ac99a7f1072a07f66b87fc09ed463876ba2f2681a5b03f21aa31

Observation 4e3742c7-26a1-4820-beaa-8c220cde2144 · outbound

This paper cites Qwen3 Technical Report.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies Qwen3 Technical Report

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:52.969311Z digest=sha256:34822241634008d6dcc2b55a0194cd726d9fcabc1a1c6b46b55efb0767009d94

Observation 1189219a-5dd6-4dd8-a199-69fe0222df11 · outbound

This paper cites online" 'onlinestring :=.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies online" 'onlinestring :=

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:53.071698Z digest=sha256:59abfe069bd161b75e50b4eae4779079da955b189cf581b040ffa6525406cfbe

Observation 7412d5f8-21d9-4ceb-a8d5-560e5a6d7dca · outbound

This paper cites write newline.

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies write newline

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:51:53.154620Z digest=sha256:273882781c45047ff5e7300b1df61c13dc6056b151f92c8db52336b4df3e3b4a

Pith citing papers

No inbound Pith citation observations are available.