Paper Citation Record · LEDGER

Looped Transformers for Length Generalization

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 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 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:12:36.387945Z

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

verified exact0
verified fuzzy0
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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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

Observation c8e0c298-f037-4b43-9b93-246d7c164a19 · inbound

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges cites this paper.

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Looped Transformers for Length Generalization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T14:54:29.153923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f7f533e-c6a0-4330-876e-f23935ea085e · inbound

Intra-Layer Recurrence in Transformers for Language Modeling cites this paper.

Intra-Layer Recurrence in Transformers for Language Modeling Looped Transformers for Length Generalization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T04:12:36.387945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: metadata mismatch; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T21:07:57.657753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-07-01T16:55:50.835789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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

Resolution: 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: metadata mismatch; 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 2026-08-20T06:33:59.587034+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:20:00.909207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.