Paper Citation Record · LEDGER

Depth-Adaptive Transformer

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:1910.10073.

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

pith.paper-citation-record.v1
1910.10073 v4

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 2026-08-14T06:32:32.682623+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:40:19.473027Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:46:28.953761Z

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 244204ad-672e-4801-ac44-df0e2c5eb2da · inbound

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding cites this paper.

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding Depth-Adaptive Transformer

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:26:44.715474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 997ddc8e-7d0b-4067-867f-0b57b2c0062e · inbound

Fast Inference from Transformers via Speculative Decoding cites this paper.

Fast Inference from Transformers via Speculative Decoding Depth-Adaptive Transformer

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:52:00.183112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 55576f29-b02f-4799-bfe5-77ecbf696086 · inbound

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models cites this paper.

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models Depth-Adaptive Transformer

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-17T02:18:02.277612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0d3f02bf-56f2-4c62-bbf7-43f9b854336c · inbound

TinyFusion: Diffusion Transformers Learned Shallow cites this paper.

TinyFusion: Diffusion Transformers Learned Shallow Depth-Adaptive Transformer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T04:40:19.473027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a1f2f3d-82ee-4962-8c77-b681aacae00f · inbound

Performance Control in Early Exiting to Deploy Large Models at the Same Cost of Smaller Ones cites this paper.

Performance Control in Early Exiting to Deploy Large Models at the Same Cost of Smaller Ones Depth-Adaptive Transformer

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T00:46:17.705612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 829eb60d-3992-4d66-9195-7bb6e8fc0855 · inbound

A Survey of Early Exit Deep Neural Networks in NLP cites this paper.

A Survey of Early Exit Deep Neural Networks in NLP Depth-Adaptive Transformer

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:40:46.185430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1f92b65-ee65-4a44-b930-b9bf5021c6f9 · inbound

Optimizing Speech Multi-View Feature Fusion through Conditional Computation cites this paper.

Optimizing Speech Multi-View Feature Fusion through Conditional Computation Depth-Adaptive Transformer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T20:35:13.040015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acd29e4c-0339-438e-a6d0-c30b2e11c871 · inbound

System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts cites this paper.

System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts Depth-Adaptive Transformer

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:38.108161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69641cf8-442b-4d45-babd-24d3018dc9fb · inbound

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

Learning to Skip the Middle Layers of Transformers Depth-Adaptive Transformer

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T22:40:53.477626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bba254c7-9c75-4049-9fac-1434aea1ca02 · inbound

Change of Thought: Adaptive Test-Time Computation cites this paper.

Change of Thought: Adaptive Test-Time Computation Depth-Adaptive Transformer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T16:28:21.495470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c694b9b-4ce1-4710-9d8f-3a0225167cdd · inbound

Extracting Visual Facts from Intermediate Layers for Mitigating Hallucinations in Multimodal Large Language Models cites this paper.

Extracting Visual Facts from Intermediate Layers for Mitigating Hallucinations in Multimodal Large Language Models Depth-Adaptive Transformer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T15:32:34.526903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dddf6d73-6888-4f22-b420-ae1a7f571457 · inbound

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting cites this paper.

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting Depth-Adaptive Transformer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T12:45:24.763365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b006ccd-1c3f-43c9-bc92-971103d98d87 · inbound

LPC-SM: Local Predictive Coding and Sparse Memory for Long-Context Language Modeling cites this paper.

LPC-SM: Local Predictive Coding and Sparse Memory for Long-Context Language Modeling Depth-Adaptive Transformer

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:25:30.978799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 033ca98c-c0c4-457c-b5d1-93522db9bb50 · inbound

ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting cites this paper.

ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting Depth-Adaptive Transformer

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:16:28.746745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e134466c-a290-402b-8e67-bd520d544699 · inbound

Compute Where it Counts: Self Optimizing Language Models cites this paper.

Compute Where it Counts: Self Optimizing Language Models Depth-Adaptive Transformer

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:46:29.499825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3da75a85-efec-4381-95ad-1f88359818f1 · inbound

Generative Recursive Reasoning cites this paper.

Generative Recursive Reasoning Depth-Adaptive Transformer

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-20T06:03:05.424758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ea88b0b7-ff16-42d2-88b3-a13f85f98a38 · inbound

Generative Recursive Reasoning cites this paper.

Generative Recursive Reasoning Depth-Adaptive Transformer

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:44:03.132077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 293c5763-19fd-4499-a5ef-31bd84c90b28 · inbound

Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference cites this paper.

Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference Depth-Adaptive Transformer

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-06-29T21:43:59.487437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f3b2df3c-3c96-4596-8b1f-587bbfc13801 · inbound

ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents cites this paper.

ToolGate: Token-Efficient Pre-Call Control for Tool-Augmented Vision-Language Agents Depth-Adaptive Transformer

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:46:28.955527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b4ee65a6-d0d6-4f95-b2f9-b5d7ab40b1ae · inbound

Adaptive Depth in Looped Transformers: Diagnosing Learned Halting Gates and Trajectory Readouts cites this paper.

Adaptive Depth in Looped Transformers: Diagnosing Learned Halting Gates and Trajectory Readouts Depth-Adaptive Transformer

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-02T08:13:28.464915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.