Paper Citation Record · LEDGER

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit

As of 10 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 4 inbound Pith citation observations for arXiv:2501.09240.

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

pith.paper-citation-record.v1
2501.09240 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:15:28.491785Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:12:59.912293Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T16:46:15.163748Z

Reference resolution

57 of 57 outbound references displayed

verified exact2
verified fuzzy9
unresolved46
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 751bc24e-2aa5-47c3-91fa-b57bb0a59825 · outbound

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

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit What learning algorithm is in-context learning? Investigations with linear models

Reference 1

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Observation 850b2601-5e83-46c8-bc7d-4735c84a836f · outbound

This paper cites maps-to” token (->). Conversely, in the trained-from-scratch transformer, task information is stored in the y token (i.e., the “label.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit maps-to” token (->). Conversely, in the trained-from-scratch transformer, task information is stored in the y token (i.e., the “label

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.254604Z

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Observation 506fe749-b885-4c55-9b4a-9d50976e33e2 · outbound

This paper cites Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Task Prompt Vectors: Effective Initialization through Multi-Task Soft-Prompt Transfer

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.233830Z

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Observation 0f972f5c-7f52-4b72-abae-c4f76631f33f · outbound

This paper cites Longformer: The Long-Document Transformer.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Longformer: The Long-Document Transformer

Reference 5

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Observation 841a9300-336d-4acb-ae70-666176c2fd9d · outbound

This paper cites Transformers generalize differently from information stored in context vs in weights.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Transformers generalize differently from information stored in context vs in weights

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.253212Z

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Observation c0d1b830-fcaa-4f2e-bac8-2c4f1a01e5b5 · outbound

This paper cites Analyzing Transformers in Embedding Space.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Analyzing Transformers in Embedding Space

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.258738Z

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Observation 14115c38-ca1e-40de-b3ef-f4c7601b3faa · outbound

This paper cites What Can Transformers Learn In-Context? A Case Study of Simple Function Classes.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.269173Z

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Observation 8fd0073d-c676-4078-9e1d-3d58c5ee5232 · outbound

This paper cites Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.274332Z

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Observation 93094e9b-4986-42cb-aa0d-c6069f91e9f1 · outbound

This paper cites Think before you speak: Training Language Models With Pause Tokens.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Think before you speak: Training Language Models With Pause Tokens

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.279307Z

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Observation 28b1809c-cb9a-4666-954e-0b782108759e · outbound

This paper cites Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Have Faith in Faithfulness: Going Beyond Circuit Overlap When Finding Model Mechanisms

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.284054Z

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Observation 5e6f5a75-19d4-4de5-8136-858dbaadc4b7 · outbound

This paper cites In-Context Learning Creates Task Vectors.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit In-Context Learning Creates Task Vectors

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.289415Z

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Observation 03e4a715-42ac-4bd5-8044-7b4a208afca8 · outbound

This paper cites Finding Visual Task Vectors.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Finding Visual Task Vectors

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.294418Z

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Observation 1c13ee11-352d-4704-8f07-83e07c774448 · outbound

This paper cites Editing Models with Task Arithmetic.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Editing Models with Task Arithmetic

Reference 17

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Observation dd88c99d-ac3b-45cb-b924-01d6d504a4d7 · outbound

This paper cites semanticscholar.org/CorpusID:254408495.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit semanticscholar.org/CorpusID:254408495

Reference 18

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Observation d08baaec-bca3-4d8d-aea3-13d44dd243c5 · outbound

This paper cites org/CorpusID:271741273.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit org/CorpusID:271741273

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.344147Z

Source-reported events for the cited work

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Observation d012e0be-3c05-401a-bcf4-145b16bd7d33 · outbound

This paper cites Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.314561Z

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Observation cba17401-f06e-4235-9bcc-1dc4a7547050 · outbound

This paper cites When can transformers compositionally generalize in-context?.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit When can transformers compositionally generalize in-context?

Reference 21

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Observation 30666b6b-eab3-4d8e-a4c7-c9fb3254bc55 · outbound

This paper cites Supervised Pretraining Can Learn In-Context Reinforcement Learning.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Supervised Pretraining Can Learn In-Context Reinforcement Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.324021Z

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Observation b8b05d93-2c5f-4ad7-8448-42d58bac416e · outbound

This paper cites Implicit In-context Learning.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Implicit In-context Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.328902Z

Source-reported events for the cited work

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Observation 08e540c3-fbe6-485c-acf1-2c5bbfe9de63 · outbound

This paper cites Dual Operating Modes of In-Context Learning.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Dual Operating Modes of In-Context Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.333268Z

Source-reported events for the cited work

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Observation edfe781f-5283-43f7-8127-8e5d2e6c7c74 · outbound

This paper cites In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.337375Z

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Observation e80988d6-b352-4ab8-b293-628c65981c70 · outbound

This paper cites GPT Understands, Too.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit GPT Understands, Too

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.341830Z

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Observation fe283fdf-e15f-490c-b50c-dac1fb675ae5 · outbound

This paper cites Does In-Context Learning Really Learn? Rethinking How Large Language Models Respond and Solve Tasks via In-Context Learning.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Does In-Context Learning Really Learn? Rethinking How Large Language Models Respond and Solve Tasks via In-Context Learning

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:15:28.841850Z

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Observation 65e0bc34-bfc1-4038-ba68-69cda10bf560 · outbound

This paper cites Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers

Reference 28

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Observation 4fdfe0d7-6034-46b5-8b17-7b01cfe871b7 · outbound

This paper cites Language Models Implement Simple Word2Vec-style Vector Arithmetic.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Language Models Implement Simple Word2Vec-style Vector Arithmetic

Reference 29

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Observation f72d7590-7a4c-4ee1-963e-25583ad2b92f · outbound

This paper cites Does learning the right latent variables necessarily improve in-context learning?.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Does learning the right latent variables necessarily improve in-context learning?

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.359605Z

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Observation 3c68c9e0-af4e-464d-8e8a-711f72b5215a · outbound

This paper cites Learning to Compress Prompts with Gist Tokens.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Learning to Compress Prompts with Gist Tokens

Reference 31

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Observation 68f38ecf-1787-4a1f-ab41-b07864d97b77 · outbound

This paper cites Transformers Can Do Bayesian Inference.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Transformers Can Do Bayesian Inference

Reference 32

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Observation 0e782682-5566-44d5-ac41-16fd64e0b938 · outbound

This paper cites LIVE: Learnable In-Context Vector for Visual Question Answering.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit LIVE: Learnable In-Context Vector for Visual Question Answering

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.373592Z

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Observation fedd93a1-5549-499d-a5e3-96a7bd6e5f2b · outbound

This paper cites Robust Concept Erasure Using Task Vectors.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Robust Concept Erasure Using Task Vectors

Reference 34

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Observation 3946ad61-eec8-46ad-8922-e2373645740c · outbound

This paper cites Investigating the Effectiveness of HyperTuning via Gisting.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Investigating the Effectiveness of HyperTuning via Gisting

Reference 35

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Observation c2fe5417-dbc2-40c8-9213-8004bfb96902 · outbound

This paper cites Blockwise Self-Attention for Long Document Understanding.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Blockwise Self-Attention for Long Document Understanding

Reference 36

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Observation abeebd98-5226-414a-a373-963e6a819852 · outbound

This paper cites Discovering modular solutions that generalize compositionally.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Discovering modular solutions that generalize compositionally

Reference 38

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Observation 35c4bf51-4627-4fb5-a0dc-a221107076f9 · outbound

This paper cites Where does In-context Translation Happen in Large Language Models.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Where does In-context Translation Happen in Large Language Models

Reference 39

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Observation eb54ad68-6d35-497b-adf4-12d5912b13ab · outbound

This paper cites What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation

Reference 40

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Observation 7e428b76-947d-432e-a27e-0f1b496cbb12 · outbound

This paper cites Function Vectors in Large Language Models.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Function Vectors in Large Language Models

Reference 41

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Observation 25c9cb9a-76ff-478a-af77-ef1deba04bb8 · outbound

This paper cites Transformers learn in-context by gradient descent.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Transformers learn in-context by gradient descent

Reference 42

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This paper cites Uncovering mesa-optimization algorithms in Transformers.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Uncovering mesa-optimization algorithms in Transformers

Reference 43

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This paper cites Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Reference 44

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This paper cites An Explanation of In-context Learning as Implicit Bayesian Inference.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit An Explanation of In-context Learning as Implicit Bayesian Inference

Reference 45

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This paper cites Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt

Reference 46

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Observation 64e2e645-84ee-4e26-b5bd-0fc051f47ffd · outbound

This paper cites Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models

Reference 47

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This paper cites Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Scaling Up Personalized Image Aesthetic Assessment via Task Vector Customization

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:28.446887Z

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

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

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

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.315708Z

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Observation 5641d13d-503b-4d9b-a70e-4a4d6ff96e11 · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit function vector,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.301122Z

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Observation 44b61a1d-988e-48c9-95cb-c358301e63a4 · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Beyond activations, task information can also be encoded in a task token Bai et al

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.284534Z

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Observation e94eec66-f2de-4c2f-9e09-375f9b193048 · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit task vector

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.269114Z

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Observation 1611cdfc-382d-4c22-9ed8-2fcc11f1183d · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:15:29.239255Z

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Observation fb691456-b235-409e-b7a1-f4e5d628191a · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:15:29.225002Z

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Observation 54e2455e-f931-48e0-88f5-7dd06fa6febf · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit S” and 256 for notation “L

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.209952Z

Source-reported events for the cited work

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Observation 61213c96-f7a2-417e-a4a5-aae8c13f9183 · outbound

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Raventos, M

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:15:29.330343Z

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Observation 72e52769-bb56-4be9-aab3-3b2270e0fd77 · outbound

This paper cites Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions

Reference 2020

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Task Vectors in In-Context Learning: Emergence, Formation, and Benefit In-context learning and Occam's razor

Reference 2021

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:15:29.064729Z

Source-reported events for the cited work

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Observation 09e07dbc-3428-452a-b94e-e8a2a66e62dd · outbound

This paper cites In-Context Language Learning: Architectures and Algorithms.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit In-Context Language Learning: Architectures and Algorithms

Reference 2022

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Observation 94295771-02f1-41d6-916d-673db3cb9df9 · outbound

This paper cites Language Models are Few-Shot Learners.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Language Models are Few-Shot Learners

Reference 2023

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This paper cites Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

Reference 2024

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Pith citing papers

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Adaptive Task Vectors for Large Language Models cites this paper.

Adaptive Task Vectors for Large Language Models Task Vectors in In-Context Learning: Emergence, Formation, and Benefit

Reference 13

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Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations cites this paper.

Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations Task Vectors in In-Context Learning: Emergence, Formation, and Benefit

Reference 24

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Next-Token Prediction Should be Ambiguity-Sensitive: A Meta-Learning Perspective cites this paper.

Next-Token Prediction Should be Ambiguity-Sensitive: A Meta-Learning Perspective Task Vectors in In-Context Learning: Emergence, Formation, and Benefit

Reference 31

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Embedding-based In-Context Prompt Training for Enhancing LLMs as Text Encoders cites this paper.

Embedding-based In-Context Prompt Training for Enhancing LLMs as Text Encoders Task Vectors in In-Context Learning: Emergence, Formation, and Benefit

Reference 47

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