Paper Citation Record · LEDGER

What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2305.19420.

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

pith.paper-citation-record.v1
2305.19420 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:23:51.527216Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:08:56.609500Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 74b37a5f-2c6d-440f-b64e-e44a8bc5c4cf · inbound

Re-examining learning linear functions in context cites this paper.

Re-examining learning linear functions in context What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 28

Resolution: malformed identifier; no resolver link, observed 2026-08-12T18:35:15.932080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ec7bbde-c529-4fb8-bc3f-cda7bd657691 · inbound

Align, Generate, Learn: A Novel Closed-Loop Framework for Cross-Lingual In-Context Learning cites this paper.

Align, Generate, Learn: A Novel Closed-Loop Framework for Cross-Lingual In-Context Learning What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T17:25:18.875880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21fa6d11-2b18-4b4c-ab48-86e958cf38d7 · inbound

Align, Generate, Learn: A Novel Closed-Loop Framework for Cross-Lingual In-Context Learning cites this paper.

Align, Generate, Learn: A Novel Closed-Loop Framework for Cross-Lingual In-Context Learning What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T17:25:18.880714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 982f6daf-278c-4cbf-8cd8-7aa6197c76a5 · inbound

Rethinking Associative Memory Mechanism in Induction Head cites this paper.

Rethinking Associative Memory Mechanism in Induction Head What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T15:06:30.845577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0003d98f-9f8d-4703-9096-be1992e0f96f · inbound

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit cites this paper.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.451307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9edf50c1-93e4-441c-bf9a-de650359d493 · inbound

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification cites this paper.

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:57:22.774584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5c074895-ccab-496c-b162-66b2f0a622a5 · inbound

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making cites this paper.

OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:23:51.527216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ae05b38-8593-4134-aaaa-a950fe7cdccb · inbound

The Role of Diversity in In-Context Learning for Large Language Models cites this paper.

The Role of Diversity in In-Context Learning for Large Language Models What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:21:39.312528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c08623d9-6cd5-4f39-bbdc-f2d3c585938f · inbound

Transformers Meet In-Context Learning: A Universal Approximation Theory cites this paper.

Transformers Meet In-Context Learning: A Universal Approximation Theory What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T10:33:43.583162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee33adb0-f18d-4a7d-9b4e-80b8cff32d75 · inbound

In-Context Learning Strategies Emerge Rationally cites this paper.

In-Context Learning Strategies Emerge Rationally What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T19:07:53.624803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8256670b-d6cc-4ed1-95df-4dbfa215d189 · inbound

MicLog: Towards Accurate and Efficient LLM-based Log Parsing via Progressive Meta In-Context Learning cites this paper.

MicLog: Towards Accurate and Efficient LLM-based Log Parsing via Progressive Meta In-Context Learning What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T11:17:08.518695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b016e28d-f34c-4967-973b-0ab877d31ab6 · inbound

Learning to Remember, Learn, and Forget in Attention-Based Models cites this paper.

Learning to Remember, Learn, and Forget in Attention-Based Models What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T03:16:08.550730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 287e5252-0bcd-42c3-87cf-cc708d708987 · inbound

Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior cites this paper.

Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 237

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:16:06.653461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ec4cb987-ef62-4cb9-8c05-2e79e679d041 · inbound

Autoregressive Learning in Joint KL: Sharp Oracle Bounds and Lower Bounds cites this paper.

Autoregressive Learning in Joint KL: Sharp Oracle Bounds and Lower Bounds What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T06:57:27.852462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b14c177-9aa5-4546-8ce4-1eba8ddea6ea · inbound

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space cites this paper.

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:27:19.214954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d80ba75c-3202-45ab-b2dd-62ea4f4e46d7 · inbound

TabQL: In-Context Q-Learning with Tabular Foundation Models cites this paper.

TabQL: In-Context Q-Learning with Tabular Foundation Models What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:38:16.860361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b08f4ee-a0ad-4eb9-83ff-02c8a96e0954 · inbound

Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning cites this paper.

Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.580390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8634f9fe-dde4-4250-a196-3f47536739e1 · inbound

DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination cites this paper.

DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T20:57:23.813717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ce37460c-19f7-4e64-920f-b7227c3393ea · inbound

From Drift to Coherence: Stabilizing Beliefs in LLMs cites this paper.

From Drift to Coherence: Stabilizing Beliefs in LLMs What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T20:08:56.612321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 99b9dea2-1db0-4de7-95c2-6a41916d8301 · inbound

Sequential Correlations Change In-Context Learning: Effective Context Length and Architectural Mismatch cites this paper.

Sequential Correlations Change In-Context Learning: Effective Context Length and Architectural Mismatch What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-12T00:51:41.905788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dcb898f-d340-4982-b923-5f96ff270adb · inbound

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex cites this paper.

Training with (Swap) Regret Loss in a Single-Layer Self-Attention Model: A Case Study on the Probability Simplex What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization

Reference 228

Resolution: unresolved; no resolver link, observed 2026-07-31T23:52:09.821439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.