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Paper Citation Record · LEDGER

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2208.01066.

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

pith.paper-citation-record.v1
2208.01066 v3

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 2026-08-07T06:34:17.273281+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:38:35.365797Z

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

59
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 cdb9c244-c02e-47b9-beed-8cabd65cd457 · inbound

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? cites this paper.

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 188

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T09:51:46.854596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-15T09:51:46.701149Z digest=sha256:5b60239e9549b649e25372a11eea7aca36a6679373bfadf97439c129c62742fa

Observation cf00f16e-5150-4bcb-8946-e16abb949c1b · inbound

What learning algorithm is in-context learning? Investigations with linear models cites this paper.

What learning algorithm is in-context learning? Investigations with linear models What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 11

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verified exact
arxiv_id, observed 2026-05-17T13:40:33.945147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-17T13:40:33.889712Z digest=sha256:416aafda13b0f74485db88e3d896551171b0268ea220b1a91088c547ccc768c2

Observation ea4dc51c-bfae-4043-ae2b-682ddb3ae7c1 · inbound

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data cites this paper.

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 171

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verified exact
arxiv_id, observed 2026-05-20T13:35:02.244418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T13:35:02.018244Z digest=sha256:132256659be6ea861e9da02992879c0b5964401bc8de4f88d5287331f24814c5

Observation 024cab8f-b061-4b05-92cd-9b2032aa1505 · inbound

Eliciting Fine-Tuned Transformer Capabilities via Inference-Time Techniques cites this paper.

Eliciting Fine-Tuned Transformer Capabilities via Inference-Time Techniques What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 16

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no resolver link, observed 2026-08-07T05:38:35.365797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:38:35.365797Z digest=sha256:0d57cb98237caea70f8e0e41289bcb62f810c249a918a205c907059fb8881b97

Observation 83f1bbe1-ef29-4705-89d6-2d22e9a75762 · inbound

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models cites this paper.

Thinking About Thinking: SAGE-nano's Inverse Reasoning for Self-Aware Language Models What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 77

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unresolved
no resolver link, observed 2026-08-06T21:38:16.041875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:38:16.041875Z digest=sha256:b50f3d27be4d75e59b694c21b756f63dfe561ab68d11b904e9da03e93784ba62

Observation 258ea24e-1585-4f6f-8387-22cc6fcad34b · inbound

Context Tuning for In-Context Optimization cites this paper.

Context Tuning for In-Context Optimization What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 16

Resolution
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no resolver link, observed 2026-08-06T19:59:19.613893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:59:19.613893Z digest=sha256:401d4bb10fc7693c3ea717396e4bbcaf6e4187bf3e107b91cbf0f4af1d261caf

Observation 949a9976-c58b-4668-aba9-159d7e45e536 · inbound

Transformers Don't In-Context Learn Least Squares Regression cites this paper.

Transformers Don't In-Context Learn Least Squares Regression What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 8

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no resolver link, observed 2026-08-06T18:03:14.943494Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:03:14.943494Z digest=sha256:3c32488b95fabffdda4861b6b1903c8b6349afd737543a730b4bc65e4b416e67

Observation 61bfdefd-a9c0-4be3-9bd8-766e28e29ed0 · inbound

LLMs are Bayesian, In Expectation, Not in Realization cites this paper.

LLMs are Bayesian, In Expectation, Not in Realization What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 5

Resolution
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no resolver link, observed 2026-08-06T17:10:01.336608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:10:01.336608Z digest=sha256:58a4a9d60b23ca3994c05e9822eaf0d10f52ba3b798794ef2e7a73961aa01cd1

Observation 5c67e761-1f4e-45f8-b811-9a54c4d75257 · inbound

Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need cites this paper.

Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 34

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no resolver link, observed 2026-08-06T16:17:41.267606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:17:41.267606Z digest=sha256:903fa64e86365ba1007e38566f71fb7714d701aef8e23c3e8717e805257e2f7c

Observation 5decba14-dac5-43e8-8709-73a644e97584 · inbound

Customizing the Inductive Biases of Softmax Attention using Structured Matrices cites this paper.

Customizing the Inductive Biases of Softmax Attention using Structured Matrices What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 19

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unresolved
no resolver link, observed 2026-08-04T21:33:56.521170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T21:33:56.521170Z digest=sha256:744fd82387562cd8a5018baf22882a89121fee6b2e8b1508cb74f7c58204d132

Observation fcc74421-141d-4bda-9901-5c42464dc153 · inbound

ICR-RL: Deep Reinforcement Learning via In-Context Regression cites this paper.

ICR-RL: Deep Reinforcement Learning via In-Context Regression What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T16:52:10.272420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T16:52:10.272420Z digest=sha256:5ebc0d463e0cba89244182d7adeb62b4a9366a7bc36586624678e4197a064cd2

Observation 4f11315c-2e1f-4c7c-8bc7-61d0ff547523 · inbound

Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability cites this paper.

Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 7

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no resolver link, observed 2026-08-04T07:21:34.326253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:21:34.326253Z digest=sha256:1f779c7b301c7b6a1e73d85a0dd2a2b0241a561a4bd5327b1d54d4910ab7a7c7

Observation ff40bd46-9ffb-4523-8ac8-07950662b932 · inbound

Jacobian Scopes: token-level causal attributions in LLMs cites this paper.

Jacobian Scopes: token-level causal attributions in LLMs What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T08:38:37.436234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T08:38:37.436234Z digest=sha256:36eba67c81776959962cffd0ee24b10c26c991d99c74b91bb5aec7cb24dcc717

Observation f3f7adea-80df-457c-9be5-c6befcb79191 · inbound

When Context Sticks: Studying Interference in In-Context Learning cites this paper.

When Context Sticks: Studying Interference in In-Context Learning What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:36:09.546744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T08:31:14.231710Z digest=sha256:94eb58d7183b38f377424d93cf7b56c40c40e52ec91d8fcd51c296de47a35ce6

Observation 5e083d39-ecb2-4e7c-8d1d-6ec57a794724 · inbound

Spectral Transformer Neural Processes cites this paper.

Spectral Transformer Neural Processes What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:41:34.613699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T04:04:14.880310Z digest=sha256:45ef3c322a2d5d567972ed95e6055deb6ba0866d0cfb6eaf60de9d23039c8e22

Observation 9375efff-722e-483a-9844-b7ac7a0e4793 · inbound

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning cites this paper.

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:56:32.102101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T03:46:21.786972Z digest=sha256:a488dd680e3b960dc26bb1bf27dba9797bcd475d452589cc861f50244af63663

Observation a14008e6-f011-4c9b-ad2a-15400aa997af · inbound

Consistency Training while Mitigating Obfuscation via Rate Matching cites this paper.

Consistency Training while Mitigating Obfuscation via Rate Matching What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 120

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verified exact
arxiv_id, observed 2026-06-28T14:32:18.122600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T14:25:43.147442Z digest=sha256:0b1529f1bf478e453e9d22c18d6c458ee846d48f1fef901112dea173b80d1f09

Observation b75008fa-e823-4c9d-a88c-0b752f9070cd · inbound

Pretraining Curricula Enable Selective Fine-tuning cites this paper.

Pretraining Curricula Enable Selective Fine-tuning What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 16

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unresolved
no resolver link, observed 2026-07-11T12:36:24.747752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T12:36:24.747752Z digest=sha256:a811f0be743130a9df135b3300861a308a7440924392eb9d9f299fbcfdfed94f

Observation 9237aa7a-a605-49ac-93e5-d11e4f3e1dac · inbound

In-context learning of closed form solution to simple linear regression task using transformer with linear self-attention cites this paper.

In-context learning of closed form solution to simple linear regression task using transformer with linear self-attention What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 5

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no resolver link, observed 2026-08-01T22:19:53.798648Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:19:53.798648Z digest=sha256:aae8447f305b7c9819078efc66f5e38dbd9492f3cc855380e5912cb805362b05

Observation aeb88158-ecf7-49e0-8a70-a6bc81f1f4eb · inbound

Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners cites this paper.

Entangled by Design: Spurious Intra-Variable Signal Routing in Tabular In-Context Learners What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 2022

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no resolver link, observed 2026-08-01T02:16:26.987736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T02:16:26.987736Z digest=sha256:2ce11498722ce277ebb07efd6654eec741295fd9138f65f79ea050945324f2b0