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Paper Citation Record · LEDGER

Looped Transformers for Length Generalization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2409.15647.

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

pith.paper-citation-record.v1
2409.15647 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:02:55.822433Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation bdda9707-04f1-43ce-9b4f-1fa81a7ed874 · inbound

Training Large Language Models to Reason in a Continuous Latent Space cites this paper.

Training Large Language Models to Reason in a Continuous Latent Space Looped Transformers for Length Generalization

Reference 8

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arxiv_id, observed 2026-05-11T10:29:05.622707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T10:29:05.384381Z digest=sha256:97e875fc67333d5eff02524417b50e5f9a86b2674e338be13a5123f00205eb12

Observation 3c632ece-aebe-49ba-81de-8d501af621e5 · inbound

Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned Reasoning cites this paper.

Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned Reasoning Looped Transformers for Length Generalization

Reference 2019

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no resolver link, observed 2026-08-08T05:02:55.822433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:02:55.822433Z digest=sha256:7afac3f11026612617240ccc85c9c229ab2bcc95240847476817febc1ab18834

Observation 18ca2c93-1902-4af6-bec1-5eca8dbfa16a · inbound

SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought cites this paper.

SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought Looped Transformers for Length Generalization

Reference 23

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no resolver link, observed 2026-08-07T12:39:00.469205Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:39:00.469205Z digest=sha256:f03d8ce9d56df400cee71c735736e91c66020396f58a29048b8e99367dc48c7b

Observation de2c2496-8001-4cab-a1ad-e9330e8993f2 · inbound

Extrapolation by Association: Length Generalization Transfer in Transformers cites this paper.

Extrapolation by Association: Length Generalization Transfer in Transformers Looped Transformers for Length Generalization

Reference 15

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no resolver link, observed 2026-08-07T04:59:21.582522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:59:21.582522Z digest=sha256:8ce3a69094753faeeb4f92b28a58bcad29f2f3c697231a0c5765308d43a201d8

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

Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs cites this paper.

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:b0c2c03cb71c79251d6babb6539ce210b41e785456d95b9c682b2110a83dc03b

Observation 405eb33a-611c-444d-98ef-14bfc541b3dc · inbound

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks cites this paper.

Channel-Wise MLPs Improve the Generalization of Recurrent Convolutional Networks Looped Transformers for Length Generalization

Reference 3

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no resolver link, observed 2026-08-06T00:01:41.852577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:01:41.852577Z digest=sha256:c6ce7cac714cd89a97ca74f61968b1d5e329eb01fbb633f6f346bc70c3b7b582

Observation 547cb5db-c348-4027-bc09-67ed8809d07b · inbound

Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner cites this paper.

Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner Looped Transformers for Length Generalization

Reference 12

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arxiv_id, observed 2026-05-18T10:16:13.990243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T10:15:10.746336Z digest=sha256:097764b866a61565c8dbc3983e183407d0e1fab142e056e094e003b027b1a0e1

Observation b604fc07-03d5-46cb-8c94-17866457a463 · inbound

LA-Sign: Looped Transformers with Geometry-aware Alignment for Skeleton-based Sign Language Recognition cites this paper.

LA-Sign: Looped Transformers with Geometry-aware Alignment for Skeleton-based Sign Language Recognition Looped Transformers for Length Generalization

Reference 11

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arxiv_id, observed 2026-05-14T21:09:28.617126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T21:09:08.571994Z digest=sha256:dbec1beda1555bf7ebc16632ceb1a07883bd1f5256a42e343d4af5404df624a7

Observation 1edccec6-8f16-4d4a-af03-f849fabdfbd6 · inbound

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication cites this paper.

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication Looped Transformers for Length Generalization

Reference 34

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arxiv_id, observed 2026-05-14T21:07:57.657753Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T21:07:37.032208Z digest=sha256:7de50a72b198980a31fbba37b5ab13e42b7b88bd0b753342349ccca8bfe3ca4d

Observation 86cacffd-caa1-46a8-bc6f-d44def29ded4 · inbound

Exploration of Fast-Slow Latent Recurrence for Train-Short, Test-Long Generalization cites this paper.

Exploration of Fast-Slow Latent Recurrence for Train-Short, Test-Long Generalization Looped Transformers for Length Generalization

Reference 1

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arxiv_id, observed 2026-05-13T22:18:21.078268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T22:14:56.746512Z digest=sha256:84211eb235af52e7be2b04be4219b755880bfd9cc037fcee7891c1024169b093

Observation 72fb99ee-82bd-4a0f-b908-cf59e92291f8 · inbound

ELT: Elastic Looped Transformers for Visual Generation cites this paper.

ELT: Elastic Looped Transformers for Visual Generation Looped Transformers for Length Generalization

Reference 16

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arxiv_id, observed 2026-05-11T07:06:00.186678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:19:22.543462Z digest=sha256:23a782f15aed4e40635ee75088fe44268f2b68638c4540f574d756e46a916d69

Observation c03e8019-6a5c-4010-88cf-7d9bc4889ff6 · inbound

ELT: Elastic Looped Transformers for Visual Generation cites this paper.

ELT: Elastic Looped Transformers for Visual Generation Looped Transformers for Length Generalization

Reference 16

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no resolver link, observed 2026-08-02T16:35:03.155910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:35:03.155910Z digest=sha256:9e7ed8f612256536ce82a093267b945b527382c520d62fa258292a4fbf285dc2

Observation 441218a9-2ed3-4888-a8ae-b08199911a77 · inbound

Do Transformers Use their Depth Adaptively? Evidence from a Relational Reasoning Task cites this paper.

Do Transformers Use their Depth Adaptively? Evidence from a Relational Reasoning Task Looped Transformers for Length Generalization

Reference 6

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arxiv_id, observed 2026-05-11T10:16:07.428196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:34:02.796850Z digest=sha256:3490f7694a6e847bec4871b0ad1f479a3736337b633bc25458f03a5492587515

Observation f6f131da-4733-447f-9d19-993d060f4fa1 · inbound

Generalization in LLM Problem Solving: The Case of the Shortest Path cites this paper.

Generalization in LLM Problem Solving: The Case of the Shortest Path Looped Transformers for Length Generalization

Reference 17

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arxiv_id, observed 2026-05-10T10:39:38.238845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T10:37:45.355872Z digest=sha256:206b4972dacabc04deecd5b6766795eaea21d025d5f6b27007dc1484c99244d6

Observation 43c64a2f-26fa-4b03-b483-e405ee0251e1 · inbound

LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction cites this paper.

LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction Looped Transformers for Length Generalization

Reference 5

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verified exact
arxiv_id, observed 2026-05-11T13:26:04.209043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T01:44:44.346732Z digest=sha256:d7a75e8c841e807d39ed6b1f83321890282f19391308ab9a6fa7bda03dd3545b

Observation aa699c43-baa0-4faf-8c66-0a5d995ee821 · inbound

LoopQ: Quantization for Recursive Transformers cites this paper.

LoopQ: Quantization for Recursive Transformers Looped Transformers for Length Generalization

Reference 8

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arxiv_id, observed 2026-05-20T22:43:50.892943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T22:41:55.787556Z digest=sha256:600c2163bd88224bdbde997dd73cd24e9d6344bc1ea9f83dd871d6eb9e47ee4c

Observation 550de911-c630-4481-826e-f976a511b394 · inbound

Simply Stabilizing the Loop via Fully Looped Transformer cites this paper.

Simply Stabilizing the Loop via Fully Looped Transformer Looped Transformers for Length Generalization

Reference 8

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arxiv_id, observed 2026-05-20T23:23:51.691208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T23:19:28.027625Z digest=sha256:b46c59f9cb779bef6d86846ea88626568c76c4b2afcffad8af4bdd42fd180432

Observation ae86a2a4-6957-42ce-af6f-020da5617f8f · inbound

Looped Diffusion Language Models cites this paper.

Looped Diffusion Language Models Looped Transformers for Length Generalization

Reference 18

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verified exact
arxiv_id, observed 2026-06-29T23:14:01.126157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T23:13:12.343355Z digest=sha256:a958a056f6b6c6e59b1413106197149b29b1ef3e0872f15e50a6b1e4ca39e8c2

Observation 12f64f99-8d90-4207-9310-f64435b45eec · inbound

Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models cites this paper.

Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models Looped Transformers for Length Generalization

Reference 7

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arxiv_id, observed 2026-07-01T16:55:50.835789Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T20:04:32.090919Z digest=sha256:599bc2910f388f6672ae686d1116df9edcf1273406495cd090f825fdef5ba862

Observation 0c6cddee-7fa1-49e8-9277-44e96a0526b6 · inbound

Anti Mode-Collapse in Mean-Field Transformer via Auxiliary Variables cites this paper.

Anti Mode-Collapse in Mean-Field Transformer via Auxiliary Variables Looped Transformers for Length Generalization

Reference 5

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verified exact
arxiv_id, observed 2026-06-29T08:53:16.114048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T08:47:00.152997Z digest=sha256:585ddf4fb1bafa52a8c17216e2c97e7b77cd5aaec646994cb8a9845d6ec7c705

Observation 2234f3c1-7deb-4244-90a5-39605e89e0ed · 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 Looped Transformers for Length Generalization

Reference 5

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verified exact
arxiv_id, observed 2026-07-02T12:36:57.352718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T01:56:34.435152Z digest=sha256:b68e21e4329345612389091311044fcd94f02532dfce0ad449ef58a8a3c0b597

Observation faa4470c-9773-4f36-afeb-44e2f5062fc4 · inbound

Recursive Scaling in Masked Diffusion Models cites this paper.

Recursive Scaling in Masked Diffusion Models Looped Transformers for Length Generalization

Reference 47

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arxiv_id, observed 2026-07-03T19:58:54.922167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T01:44:05.022187Z digest=sha256:d6beb4e2130e1a4d417d680a8ba2c6e6da69371ea060b8c8a0c4d1c2b28ba572

Observation e5a1063d-100e-41c4-b431-1e4d3ff4c2fd · inbound

Repeated Shared Access Enables Grokking, but Edit Propagation Depends on an Addressable Memory cites this paper.

Repeated Shared Access Enables Grokking, but Edit Propagation Depends on an Addressable Memory Looped Transformers for Length Generalization

Reference 8

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arxiv_id, observed 2026-07-04T01:09:18.587059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T20:43:55.740662Z digest=sha256:ab4125221106bc5dc3e9c76bf0877c4589f54d1f7e3095c7442b9ff13ecbeb68

Observation 1c30e252-caf7-4f17-b262-0336746d2023 · inbound

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients cites this paper.

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients Looped Transformers for Length Generalization

Reference 46

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arxiv_id, observed 2026-07-04T17:20:00.909207Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-25T23:45:54.283436Z digest=sha256:f019042d12a2bfea1d37d5a724af6401917b54fd4b45fb29b6ce7f5213d995e3

Observation e7600503-d615-4bf7-aa86-4448c6393ef9 · inbound

When Does Recurrence Become an Algorithm? Convergence Selection in Weight-Tied Looped Transformers cites this paper.

When Does Recurrence Become an Algorithm? Convergence Selection in Weight-Tied Looped Transformers Looped Transformers for Length Generalization

Reference 4

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no resolver link, observed 2026-08-01T10:14:10.974064Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:14:10.974064Z digest=sha256:78c85238e163ed781f1aca4fdec4610002dbe5f9dad5d64ee14bb493df2a21a5