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Paper Citation Record · LEDGER

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs

As of 10 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 3 inbound Pith citation observations for arXiv:2507.07996.

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

pith.paper-citation-record.v1
2507.07996 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:33:20.582143Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:00:48.944002Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:36:57.338642Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy8
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d7a26cbd-3509-4c66-8327-d869ad55327d · outbound

This paper cites Neural module networks.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Neural module networks

Reference 1

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no resolver link, observed 2026-08-06T18:33:18.674198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:18.674198Z digest=sha256:8307a59bd450763140b28481e38af076c50e8810c081fedaa2a2b0e339122621

Observation 1869c13a-d85f-422e-a9af-5f817c52bed5 · outbound

This paper cites Early exit optimizations for additive machine learned ranking systems.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Early exit optimizations for additive machine learned ranking systems

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:22.592653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:18.728193Z digest=sha256:ca867d08876de9f2074b89923567b8b0382109c716179753b42c7a9a3871d60f

Observation 32bceb12-cd5d-4a01-b1ae-e9b06aed766f · outbound

This paper cites Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking

Reference 3

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no resolver link, observed 2026-08-06T18:33:18.824715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:18.824715Z digest=sha256:34ec57a426ad5ca34a49fe085acfb983fdbc6c5fb4d20371577dfe2959d8b778

Observation b921a512-63f0-4d9e-9224-722786fa34d0 · outbound

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

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 4

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no resolver link, observed 2026-08-06T18:33:18.869586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:18.869586Z digest=sha256:8f95d961933ee42503732b8b7e06698cd2d13299a7cc3594e494a79f91b5a5c7

Observation 7cea9865-718d-460f-8427-48947d1a9eea · outbound

This paper cites Universal Transformers.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Universal Transformers

Reference 5

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unresolved
no resolver link, observed 2026-08-06T18:33:18.945114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:18.945114Z digest=sha256:1574b128daa69b3528068360593c7cc7ed9292ebd8d7e46f8a4e6936dd990471

Observation aabbfb14-2008-4e3f-b531-226e1d10bdcb · outbound

This paper cites Faith and fate: Limits of transformers on compositionality.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Faith and fate: Limits of transformers on compositionality

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:22.383678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:19.014231Z digest=sha256:78963714cda6310e88e14cc2f5cc9afa6e65cf88a8139c350cc684fc28dcb690

Observation b2fcee33-9d97-4b71-8394-cfd48c516dbd · outbound

This paper cites DACT-BERT: Differentiable Adaptive Computation Time for an Efficient BERT Inference.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs DACT-BERT: Differentiable Adaptive Computation Time for an Efficient BERT Inference

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:33:20.896116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:19.080315Z digest=sha256:f6d005f7b0960d11c139563fde4ade47196be6ca5e2b367966331bc1a3b146d6

Observation 54e80b2d-9a4e-45cd-b894-d3ffe7f781a1 · outbound

This paper cites Reducing Transformer Depth on Demand with Structured Dropout.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Reducing Transformer Depth on Demand with Structured Dropout

Reference 8

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no resolver link, observed 2026-08-06T18:33:19.194766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.194766Z digest=sha256:e18f29190b803861de829706c6deec2f15190401d7a6b74b1606dea3aeafc315

Observation 94078844-e10c-4e60-8423-adbe8c9346e9 · outbound

This paper cites Looped Transformers for Length Generalization.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Looped Transformers for Length Generalization

Reference 9

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no resolver link, observed 2026-08-06T18:33:19.337300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.337300Z digest=sha256:fb0af637d15102ec5930283a29b8b939271733a1aca94097856600ee07433dc2

Observation b55f4d91-cdd6-4021-a825-612084ff9d7a · outbound

This paper cites Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Reference 10

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no resolver link, observed 2026-08-06T18:33:19.442435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.442435Z digest=sha256:6f97155172990c47942001631d7486cec91a4007a881a20250d83861339311db

Observation dd5655a8-9313-466c-ba0c-fac2b049e18e · outbound

This paper cites Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning

Reference 11

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no resolver link, observed 2026-08-06T18:33:19.515978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.515978Z digest=sha256:27db5769ec228a6b26115577cfa70d8c3dbab558d5c7da0e7328079e6650e3c6

Observation cee57b3e-aadb-4b6c-a09b-6995499c7d59 · outbound

This paper cites Mixture of Nested Experts: Adaptive Processing of Visual Tokens.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Mixture of Nested Experts: Adaptive Processing of Visual Tokens

Reference 12

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unresolved
no resolver link, observed 2026-08-06T18:33:19.618801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.618801Z digest=sha256:f37c8afb9a73f1caee19813d8f0c706bebbfbc5987985cee1e07800f1623a66a

Observation a67d989e-02ae-44e7-9317-17564ded0ee2 · outbound

This paper cites FastBERT: a Self-distilling BERT with Adaptive Inference Time.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs FastBERT: a Self-distilling BERT with Adaptive Inference Time

Reference 13

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no resolver link, observed 2026-08-06T18:33:19.702829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.702829Z digest=sha256:20516c7f806a8783993401a50344c005ce89806cf601fc4ef1c02fc170e50a63

Observation 95647168-7130-41b8-b7ef-53db4423b525 · outbound

This paper cites Faster depth-adaptive transformers.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Faster depth-adaptive transformers

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:22.166579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:19.751026Z digest=sha256:b6ec012dbca185901d885a5d2685ed23773f474767fe49134909a4d682da0b5b

Observation d16d4018-06bf-469c-b2a4-dcab4e02214c · outbound

This paper cites Ebert: Efficient bert inference with dynamic structured pruning.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Ebert: Efficient bert inference with dynamic structured pruning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:21.923462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:19.829868Z digest=sha256:075741fa0dde3a8b08ebe88e9a4ccaffb64f0ba39ac344a3206a72fd532032ff

Observation 5be22ff9-fbb4-4592-98d1-6d273aaad627 · outbound

This paper cites Anytime Dense Prediction with Confidence Adaptivity.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Anytime Dense Prediction with Confidence Adaptivity

Reference 16

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no resolver link, observed 2026-08-06T18:33:19.899681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:19.899681Z digest=sha256:f64aedbbea0786841c5910edde67898427a0645e6c154fd0607525ddf6f2dc2b

Observation 6467bace-6a83-454b-bf80-d41bd7e7b32b · outbound

This paper cites On limitations of the transformer architecture.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs On limitations of the transformer architecture

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:21.734761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:19.970608Z digest=sha256:75cb8d816a0701e3cecd169a0be6570b5f219e4b63056bcf177ee11baf92c271

Observation 8181068c-b182-440f-8f3c-3b76f1043e29 · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:20.036112Z digest=sha256:2179ecb1fdb7f26f953cac611d2307750a27c18e7a6f64e77eb93815ae0fe8d4

Observation 7960cd81-b139-40c1-b0e7-5b43dcd2710a · outbound

This paper cites You need multiple exiting: Dynamic early exiting for accelerating unified vision language model.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs You need multiple exiting: Dynamic early exiting for accelerating unified vision language model

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:21.502530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:20.118401Z digest=sha256:2491e86a13963a4b2c33721c4a26889f74d291cd8683d6c430581225b1cea5ee

Observation 35ad1247-b75e-4230-8ff2-a47cf72342b0 · outbound

This paper cites Branchynet: Fast inference via early exiting from deep neural networks.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Branchynet: Fast inference via early exiting from deep neural networks

Reference 20

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no resolver link, observed 2026-08-06T18:33:20.189870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:20.189870Z digest=sha256:be77ae7d0a897b739423e76fc7a5a258559e1e36540a9de2a5439720dfce3bb1

Observation 2efbc4f3-9921-4d8b-b746-56bd1faa0354 · outbound

This paper cites DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving

Reference 21

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no resolver link, observed 2026-08-06T18:33:20.272894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:20.272894Z digest=sha256:914a131230b362fb5c75df1a06b5af224885658ee4f937b8583ae790f796d9e7

Observation d772d0ca-3939-40d3-a7f7-1b8394918ccd · outbound

This paper cites Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Routing Experts: Learning to Route Dynamic Experts in Multi-modal Large Language Models

Reference 22

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no resolver link, observed 2026-08-06T18:33:20.319719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:20.319719Z digest=sha256:e4ced2c5d2453a2c011b835c44cfa4023fda56046577ad1a9c15799580427c07

Observation 1ad0b72b-8ed4-48f1-8c13-e706fae5e322 · outbound

This paper cites DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

Reference 23

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no resolver link, observed 2026-08-06T18:33:20.378873Z

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source=pdf_text observed=2026-08-06T18:33:20.378873Z digest=sha256:5b2f8d1014268b7dc8fab6843023acc5aa0e5897e850c140b25061bd8e9528af

Observation c64381ee-1188-4625-8aa4-517ffdd3ffa8 · outbound

This paper cites Lgvit: Dynamic early exiting for accelerating vision transformer.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Lgvit: Dynamic early exiting for accelerating vision transformer

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:21.277639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:20.451573Z digest=sha256:250520fb2524df30587db32fe91d70a58fb3680d07bb215ed3fd60729b4bbc29

Observation d55f31ec-99ae-4bfe-8207-672fe36795e3 · outbound

This paper cites Looped Transformers are Better at Learning Learning Algorithms.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Looped Transformers are Better at Learning Learning Algorithms

Reference 25

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no resolver link, observed 2026-08-06T18:33:20.499325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:20.499325Z digest=sha256:e83148e5403bfabf9fda38f10d002d10d2d25541736251d95cd474eeb52155b1

Observation a8c89171-2c8a-4720-9f14-c6ae96ba4fbd · outbound

This paper cites Bert loses patience: Fast and robust inference with early exit.

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs Bert loses patience: Fast and robust inference with early exit

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:33:21.105730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T18:33:20.582143Z digest=sha256:856a93f9ece8398d98f71caea84ba1059a934b8ab55e0c0d6e6c6bcc7b614d66

Pith citing papers

Observation 8468b482-8a3c-4a7c-8aed-3c8825e93da9 · inbound

Dr.LLM: Dynamic Layer Routing in LLMs cites this paper.

Dr.LLM: Dynamic Layer Routing in LLMs Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:04:20.298986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T20:01:48.806709Z digest=sha256:24b2577a03b74f25839aa4e9fd715784fb43165c587f730faa4d2685eba06bb1

Observation da8f35f1-6a78-44dc-8505-e22bebcc4ddd · inbound

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs cites this paper.

Skip a Layer or Loop It? Learning Program-of-Layers in LLMs Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:36:57.341253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T01:56:34.435152Z digest=sha256:d00f4f1338174a127027e671dd7d570390144ff9b4b5c4a72aa691b04d4bf6ef

Observation f25bee59-153a-4efb-b85a-4f65d9f843e3 · inbound

MACRO: Markov Chain Routing of Transformer Layers cites this paper.

MACRO: Markov Chain Routing of Transformer Layers Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs

Reference 21

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unresolved
no resolver link, observed 2026-08-07T22:00:48.944002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T22:00:48.944002Z digest=sha256:8d11c5ec4be8dbeacdc33a9368ac738ae90aa833ea6ee935540a3f5a2169e31a