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Paper Citation Record · LEDGER

Looped Transformers are Better at Learning Learning Algorithms

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2311.12424.

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

pith.paper-citation-record.v1
2311.12424 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 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 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:14:47.520785Z

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 ac5546ec-9df7-4b56-ab61-5bdf12648fba · inbound

A Survey on Large Language Models for Mathematical Reasoning cites this paper.

A Survey on Large Language Models for Mathematical Reasoning Looped Transformers are Better at Learning Learning Algorithms

Reference 95

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no resolver link, observed 2026-08-07T05:14:47.520785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:47.520785Z digest=sha256:13eb5b73623c9515c1be4ca4ae246784b22f0ce5b3b3f08aa7d89ca6e56d73e8

Observation 7baf9805-b726-47c2-987a-4119f5be4ac3 · inbound

Fast and Simplex: 2-Simplicial Attention in Triton cites this paper.

Fast and Simplex: 2-Simplicial Attention in Triton Looped Transformers are Better at Learning Learning Algorithms

Reference 43

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unresolved
no resolver link, observed 2026-08-06T20:31:47.992493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:31:47.992493Z digest=sha256:5aa63e5f3911d2c21563c8cce621f2d79c51ccf5be2afd97d58c383f9818fc94

Observation d55f31ec-99ae-4bfe-8207-672fe36795e3 · 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 are Better at Learning Learning Algorithms

Reference 25

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unresolved
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:bf2ab533d432222bef45b92d3cf782e588dc474c5f16f2fe7916515c6f6c343e

Observation b9b74d5d-665c-43f4-9b29-319a00aed38e · inbound

Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling cites this paper.

Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling Looped Transformers are Better at Learning Learning Algorithms

Reference 73

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verified exact
arxiv_id, observed 2026-05-18T20:51:50.783909Z

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=pdf_text observed=2026-05-18T20:49:26.966293Z digest=sha256:e499cb62b8c092a41779691e19c0a6f6263bb10e9bb378ac8ffa26bb4340cf10

Observation b3344619-5ac2-4f1c-902f-6e11c86e0e45 · inbound

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

Dr.LLM: Dynamic Layer Routing in LLMs Looped Transformers are Better at Learning Learning Algorithms

Reference 20

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arxiv_id, observed 2026-05-21T20:04:20.322992Z

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=pdf_text observed=2026-05-21T20:01:48.806709Z digest=sha256:8c1ce265f585978f638f9fb483a1aa73e97698ffe64855b9809363ef7eaaef06

Observation db66b97e-dea3-4dbc-9e00-e7702aea514c · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 14

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verified exact
arxiv_id, observed 2026-05-15T07:43:11.911968Z

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=pdf_text observed=2026-05-15T07:43:11.620446Z digest=sha256:02f7d6adf8dd51da2499eebab252596053697489a31bef892f4492cfdd58f59c

Observation d1a238ee-4dfc-455e-8966-3ed5eb746f64 · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T07:31:11.348348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:31:11.348348Z digest=sha256:7f359d7d6d353713b53bb7c2ba63ef3f82ffd55b1bfb97853257948b10c93499

Observation f05a28e1-9b46-4a09-90ea-5f15886d9229 · inbound

Latent Reasoning in TRMs is Secretly a Policy Improvement Operator cites this paper.

Latent Reasoning in TRMs is Secretly a Policy Improvement Operator Looped Transformers are Better at Learning Learning Algorithms

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T21:06:30.161963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:06:30.161963Z digest=sha256:6137f9d963b8bc85ae3806c8ffa0459b3dabb0acbab13124582fef029d499149

Observation 52f26761-85b8-4931-b7c4-f7990128c0c8 · inbound

Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning cites this paper.

Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning Looped Transformers are Better at Learning Learning Algorithms

Reference 40

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unresolved
no resolver link, observed 2026-07-15T12:09:16.468055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T12:09:16.468055Z digest=sha256:2f28c0e2ab2a783bd000c340ca30b72213bfa7d7ebbe930f6c5e904ecd897ab8

Observation 1a52b37d-f2a8-42a4-90c4-04421df42e89 · inbound

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

ELT: Elastic Looped Transformers for Visual Generation Looped Transformers are Better at Learning Learning Algorithms

Reference 79

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verified exact
arxiv_id, observed 2026-05-11T07:06:00.069258Z

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=pdf_text observed=2026-05-10T17:19:22.543462Z digest=sha256:b74d7bd45fb19f570ae7191db0e223c4c507a3d2d2c88e31da86f0153db84969

Observation c381031a-4e2b-4f29-9acd-b300de2f44c9 · inbound

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

ELT: Elastic Looped Transformers for Visual Generation Looped Transformers are Better at Learning Learning Algorithms

Reference 75

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no resolver link, observed 2026-08-02T16:35:03.415864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:35:03.415864Z digest=sha256:fe4a701596e2d8effaeacb72936814d2d723311b6d5ccc299c9a89e825c7b8f2

Observation 31921472-32b9-46a1-bc72-4cf406615250 · inbound

A Mechanistic Analysis of Looped Reasoning Language Models cites this paper.

A Mechanistic Analysis of Looped Reasoning Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 32

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verified exact
arxiv_id, observed 2026-05-11T09:41:02.876059Z

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=pdf_text observed=2026-05-10T15:53:19.680424Z digest=sha256:718be51078ceeb690eb1acb386eb0127e3544389a6cc2e0455b78a12964f2ef3

Observation 43603986-8bb0-43de-92a8-5773eda409a9 · inbound

Parcae: Scaling Laws For Stable Looped Language Models cites this paper.

Parcae: Scaling Laws For Stable Looped Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 88

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arxiv_id, observed 2026-05-11T10:21:01.161581Z

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=pdf_text observed=2026-05-10T15:33:04.442462Z digest=sha256:a73b26191cb2af0260fc16e576cdbed01486d0bf483a6ebe88679b2397049a8c

Observation b6054488-d2eb-4ff5-a763-8ef5437f399a · inbound

Stability and Generalization in Looped Transformers cites this paper.

Stability and Generalization in Looped Transformers Looped Transformers are Better at Learning Learning Algorithms

Reference 23

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verified exact
arxiv_id, observed 2026-05-10T12:25:22.705878Z

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=pdf_text observed=2026-05-10T12:21:16.015362Z digest=sha256:7701d5367dda3da6e6aeb8a1aab2c7116aa19b126f579fc427a23ee8e4184f4f

Observation 73035e9e-ba65-4284-ba4c-c9b39f1056e4 · inbound

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models cites this paper.

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models Looped Transformers are Better at Learning Learning Algorithms

Reference 213

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verified exact
arxiv_id, observed 2026-05-10T11:05:09.039941Z

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=2026-05-10T04:56:35.796962Z digest=sha256:b9cf9252537a436d5b5c8b2a2c6f022f182c59c7b0af89fa1a0f5fea0878c9bd

Observation 569ef911-975d-46cf-85e5-a1d0c5f74f1f · inbound

Hyperloop Transformers cites this paper.

Hyperloop Transformers Looped Transformers are Better at Learning Learning Algorithms

Reference 28

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arxiv_id, observed 2026-05-11T14:16:04.406242Z

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=pdf_text observed=2026-05-09T23:09:35.640412Z digest=sha256:39f2073ec8366f227ba9c6a5a228700e79192741c452b7e8229cbb47e44cf8af

Observation fe12ed9a-f66f-4efa-9fa8-c276beb8bebe · inbound

Revisiting Transformer Layer Parameterization Through Causal Energy Minimization cites this paper.

Revisiting Transformer Layer Parameterization Through Causal Energy Minimization Looped Transformers are Better at Learning Learning Algorithms

Reference 20

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verified exact
arxiv_id, observed 2026-05-11T03:45:59.117926Z

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=pdf_text observed=2026-05-11T02:17:32.226166Z digest=sha256:a1ff11a814666734af4e66f32d08dc5dea12205b7b51c3a874f099d8fdc33092

Observation e8ddfa5d-10cd-4553-b6d3-1c76b514440d · inbound

Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models cites this paper.

Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 12

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malformed identifier
arxiv_id, observed 2026-05-11T02:45:57.716481Z

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=pdf_text observed=2026-05-11T02:44:36.697450Z digest=sha256:0f0564bfea95d8e5c495b3364eb60c1c73e9e413ffc6dedb2bc6aba1ea54a353

Observation 1c218afb-52a6-4e0b-986e-27ab182ee108 · inbound

Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models cites this paper.

Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 12

Resolution
malformed identifier
arxiv_id, observed 2026-05-20T23:03:50.651160Z

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=pdf_text observed=2026-05-20T23:01:17.957634Z digest=sha256:d601febcbf5586ea6792f662adc95a286eb2f30128ded1680b91e597982f61d8

Observation 3551defe-cbb4-421c-814c-4e3073f3fa90 · inbound

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

Simply Stabilizing the Loop via Fully Looped Transformer Looped Transformers are Better at Learning Learning Algorithms

Reference 12

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verified exact
arxiv_id, observed 2026-05-20T23:23:51.684336Z

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=2026-05-20T23:19:28.027625Z digest=sha256:7aa2191df8353f862fb79c67b6da5cf08f7d4ee50671f2acb270f006e53e0f9f

Observation 3b1fd5bd-2445-47b0-839f-b2140b0b7226 · inbound

Generative Recursive Reasoning cites this paper.

Generative Recursive Reasoning Looped Transformers are Better at Learning Learning Algorithms

Reference 7

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verified exact
arxiv_id, observed 2026-05-20T06:03:05.463229Z

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=pdf_text observed=2026-05-20T05:58:23.543870Z digest=sha256:e8120c62857ebd0122b2b374803e884899b493ff29339676a8d8e680e5bcccc8

Observation 8a8dd166-6c65-4af3-9702-5e4eae77798f · inbound

Generative Recursive Reasoning cites this paper.

Generative Recursive Reasoning Looped Transformers are Better at Learning Learning Algorithms

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:44:03.156867Z

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=pdf_text observed=2026-05-21T07:40:30.199868Z digest=sha256:641edd67feee38bc5192c11363cacb25b8f66bf07ce695298132fdf9ac205c2c

Observation a6e68ede-ad75-41ad-b49f-088426e09b66 · inbound

Looped Diffusion Language Models cites this paper.

Looped Diffusion Language Models Looped Transformers are Better at Learning Learning Algorithms

Reference 74

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arxiv_id, observed 2026-06-29T23:14:01.184995Z

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=pdf_text observed=2026-06-29T23:13:12.343355Z digest=sha256:d7152fbdf2f2e0e73eb5187978df21963209ee24b328a8a305e438f698d248ef

Observation 9957a063-9204-423c-9b06-2d22fc0f5c8e · 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 are Better at Learning Learning Algorithms

Reference 21

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verified exact
arxiv_id, observed 2026-07-01T16:55:50.838803Z

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=pdf_text observed=2026-06-29T20:04:32.090919Z digest=sha256:5b9039cf0aebc36ebfb373618113afbf3373962230d9bbb56031c938a7de1ad4

Observation fd9c3b51-829e-4261-ab83-584983581290 · 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 are Better at Learning Learning Algorithms

Reference 15

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verified exact
arxiv_id, observed 2026-07-02T12:36:57.360001Z

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=pdf_text observed=2026-06-28T01:56:34.435152Z digest=sha256:51a9316f3d7cef88c55fc767978fe166ca3ba29dcf9e189e854a25b42760d0b8

Observation 1084b777-ea73-4ac9-9046-56a4404a6605 · inbound

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory cites this paper.

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory Looped Transformers are Better at Learning Learning Algorithms

Reference 114

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verified exact
arxiv_id, observed 2026-07-02T11:46:55.246863Z

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=pdf_text observed=2026-06-28T03:07:52.730713Z digest=sha256:4f65021f6f052812667340faa6b95d20fdc8cb0e03f0eaa890db3b37f9ad8f66

Observation 43d26cc0-a137-4cff-9282-77c60f3b052c · inbound

Recursive Scaling in Masked Diffusion Models cites this paper.

Recursive Scaling in Masked Diffusion Models Looped Transformers are Better at Learning Learning Algorithms

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:58:54.919466Z

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=2026-06-27T01:44:05.022187Z digest=sha256:427e382dac3e2cdcfe0eed5ecbc5fc24aa09de2d7b54f753324af2b14711e250

Observation eee62f3c-a5a5-4ef0-92c9-68408c9250b9 · inbound

Looped World Models cites this paper.

Looped World Models Looped Transformers are Better at Learning Learning Algorithms

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T19:28:52.391390Z

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=pdf_text observed=2026-06-27T01:49:57.105358Z digest=sha256:bdb8984daf3a20ecc32c6e2b5d8f2cd24486fafa1fea8830d11eb5d39a4b2653

Observation b15ff817-c0ff-4df8-8d55-fe8c76a7a16c · inbound

Looped World Models cites this paper.

Looped World Models Looped Transformers are Better at Learning Learning Algorithms

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-06-27T01:50:21.199353Z

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=pdf_text observed=2026-06-27T01:49:57.105358Z digest=sha256:0d70104130278fac5412e0b1f25f6a1f0ab92d1c06dd16d64a2e481e4d570c4e

Observation 9a756ddc-2c12-40c6-abf3-478c746104a7 · inbound

Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping cites this paper.

Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping Looped Transformers are Better at Learning Learning Algorithms

Reference 15

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verified exact
arxiv_id, observed 2026-06-30T07:34:20.928414Z

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=pdf_text observed=2026-06-30T07:29:23.786653Z digest=sha256:329d0a5372fb8ac7a123071d2f1f5aabe422a58f41c175e12e59991eb476e835

Observation ee72711e-bd43-474d-b726-73b7fc11920f · 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 Looped Transformers are Better at Learning Learning Algorithms

Reference 29

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unresolved
no resolver link, observed 2026-08-02T08:13:30.565694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:13:30.565694Z digest=sha256:84169b3e20032debe8e60d34c0276a4111364aafc4559a45c73bd357d02c44ad

Observation 41107749-7689-400b-b356-323262ca2c0b · 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 are Better at Learning Learning Algorithms

Reference 2022

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unresolved
no resolver link, observed 2026-08-01T10:14:11.657461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:14:11.657461Z digest=sha256:a0be9151acc9595ff4097f679fd67d791639a4bc39072327b9ac8b7458c5dfe5