Paper Citation Record · LEDGER

ICLR: In-Context Learning of Representations

As of 10 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 12 inbound Pith citation observations for arXiv:2501.00070.

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

pith.paper-citation-record.v1
2501.00070 v2

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:24:01.701539Z

measured 90 of 90 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:52:24.247836Z

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

78 of 78 outbound references displayed

verified exact0
verified fuzzy24
unresolved54
parse uncertain0
malformed identifier0
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External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation a61acc38-7580-4c34-9485-5a2964d8e8a1 · outbound

This paper cites Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color.

ICLR: In-Context Learning of Representations Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.378299Z

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Observation 041dacfa-210f-4600-a508-91f1a26afddb · outbound

This paper cites Many-Shot In-Context Learning.

ICLR: In-Context Learning of Representations Many-Shot In-Context Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.383674Z

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Observation 5b2ce1a6-f22f-49c4-81eb-dd9eedbc0930 · outbound

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

ICLR: In-Context Learning of Representations What learning algorithm is in-context learning? Investigations with linear models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.387784Z

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Observation 986467b8-8129-401c-9454-e4f05ff4933e · outbound

This paper cites Physics of Language Models: Part 3.1, Knowledge Storage and Extraction.

ICLR: In-Context Learning of Representations Physics of Language Models: Part 3.1, Knowledge Storage and Extraction

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.392192Z

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Observation 1cf46890-2a53-4aca-ac59-b197752c6abf · outbound

This paper cites Physics of Language Models: Part 1, Learning Hierarchical Language Structures.

ICLR: In-Context Learning of Representations Physics of Language Models: Part 1, Learning Hierarchical Language Structures

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.396438Z

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Observation 194a94c7-ae30-40d6-8aec-33a4bee8358f · outbound

This paper cites Many-shot jailbreaking.

ICLR: In-Context Learning of Representations Many-shot jailbreaking

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.964759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bc7c5116-8375-439c-bad3-d69239c2b966 · outbound

This paper cites Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet, 2024.

ICLR: In-Context Learning of Representations Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.950904Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 09d2549d-ebf6-4c6d-8f95-e90db1e1628a · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

ICLR: In-Context Learning of Representations Refusal in Language Models Is Mediated by a Single Direction

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.409601Z

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Observation e9f69897-4df2-4976-abc0-7e21fe6cdbb9 · outbound

This paper cites In-Context Learning Dynamics with Random Binary Sequences.

ICLR: In-Context Learning of Representations In-Context Learning Dynamics with Random Binary Sequences

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.413522Z

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Observation c7987213-9000-40b7-8010-c9a60c01eec4 · outbound

This paper cites Semantics, conceptual role.

ICLR: In-Context Learning of Representations Semantics, conceptual role

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.937013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fa776a47-cc3f-47d4-bfd9-450e7d399e12 · outbound

This paper cites Compression in visual working memory: using statistical regularities to form more efficient memory representations.

ICLR: In-Context Learning of Representations Compression in visual working memory: using statistical regularities to form more efficient memory representations

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.921903Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f5b88c37-71b9-4964-8cdb-d27122b5c549 · outbound

This paper cites Language models are few-shot learners.

ICLR: In-Context Learning of Representations Language models are few-shot learners

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.425803Z

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Observation bf7b8024-154c-4095-8aa7-02c740577e1a · outbound

This paper cites Discovering Latent Knowledge in Language Models Without Supervision.

ICLR: In-Context Learning of Representations Discovering Latent Knowledge in Language Models Without Supervision

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.429703Z

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Observation 25edca5c-9dd1-435d-bbb7-afeee542aa90 · outbound

This paper cites Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations.

ICLR: In-Context Learning of Representations Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.433607Z

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Observation 149d1d57-ee48-4685-a794-592a24de9e36 · outbound

This paper cites The Llama 3 Herd of Models.

ICLR: In-Context Learning of Representations The Llama 3 Herd of Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.437730Z

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Observation a8055c1c-0c4d-4676-b528-4b47258fb230 · outbound

This paper cites Not All Language Model Features Are One-Dimensionally Linear.

ICLR: In-Context Learning of Representations Not All Language Model Features Are One-Dimensionally Linear

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.441554Z

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Observation ba12801a-3bba-4408-88fe-0e36bc454074 · outbound

This paper cites On a theorem of weyl concerning eigenvalues of linear transformations i.

ICLR: In-Context Learning of Representations On a theorem of weyl concerning eigenvalues of linear transformations i

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.892132Z

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Observation aa120fcf-7586-4618-ad2f-3244df00b3b3 · outbound

This paper cites NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals.

ICLR: In-Context Learning of Representations NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.448947Z

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Observation 6f14a47b-d205-41f3-8f57-70e97f3b1491 · outbound

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

ICLR: In-Context Learning of Representations What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.453205Z

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Observation a6c983ca-3945-482d-8b6f-ae56e9c57e2a · outbound

This paper cites A map of abstract relational knowledge in the human hippocampal--entorhinal cortex.

ICLR: In-Context Learning of Representations A map of abstract relational knowledge in the human hippocampal--entorhinal cortex

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.878460Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ad727de8-6240-4260-b768-cecf5a44534c · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

ICLR: In-Context Learning of Representations Gemma 2: Improving Open Language Models at a Practical Size

Reference 21

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Observation 24970903-99df-4cfb-9b29-5c32c1ca0b61 · outbound

This paper cites Abrupt Learning in Transformers: A Case Study on Matrix Completion.

ICLR: In-Context Learning of Representations Abrupt Learning in Transformers: A Case Study on Matrix Completion

Reference 22

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Observation ec760f06-c1b1-4b13-bfa2-1bcd874bf5a7 · outbound

This paper cites Language Models Represent Space and Time.

ICLR: In-Context Learning of Representations Language Models Represent Space and Time

Reference 23

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Observation ac1f9785-4695-452a-9390-22a7bd1d80f9 · outbound

This paper cites World Models.

ICLR: In-Context Learning of Representations World Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.471416Z

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Observation 3ab41d5b-6e1a-4860-bcc7-2ce1d6a06ddd · outbound

This paper cites Conceptual role semantics.

ICLR: In-Context Learning of Representations Conceptual role semantics

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.859805Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4951190f-6eb4-469e-b8ee-4feac1c2f77b · outbound

This paper cites In-context learning creates task vectors.

ICLR: In-Context Learning of Representations In-context learning creates task vectors

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.479263Z

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Observation 760cd474-697e-47ab-a26e-236f863e1867 · outbound

This paper cites Hooyberghs, B.

ICLR: In-Context Learning of Representations Hooyberghs, B

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.844983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 14c943d6-00c6-4c7f-b1d7-5c59e01f7a74 · outbound

This paper cites Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks.

ICLR: In-Context Learning of Representations Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.487532Z

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Observation 7aa066f0-da58-49f4-a2d2-5259547a0168 · outbound

This paper cites Evidence of Learned Look-Ahead in a Chess-Playing Neural Network.

ICLR: In-Context Learning of Representations Evidence of Learned Look-Ahead in a Chess-Playing Neural Network

Reference 29

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Observation 9a436826-2237-46fe-b591-df1f6fc041f7 · outbound

This paper cites Linear Connectivity Reveals Generalization Strategies.

ICLR: In-Context Learning of Representations Linear Connectivity Reveals Generalization Strategies

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.495423Z

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Observation 0f90dcfb-6c6a-4007-a9f4-dd183fe6d718 · outbound

This paper cites Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model.

ICLR: In-Context Learning of Representations Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.503204Z

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Observation cbc9cd22-26e0-4557-8573-83a709d07658 · outbound

This paper cites In-context Reinforcement Learning with Algorithm Distillation.

ICLR: In-Context Learning of Representations In-context Reinforcement Learning with Algorithm Distillation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.508312Z

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Observation 943ab309-e513-4d18-a5dd-eac081c05e0f · outbound

This paper cites A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity.

ICLR: In-Context Learning of Representations A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.513222Z

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Observation c53ed356-5273-4351-8af3-d9c6402866c9 · outbound

This paper cites Supervised pretraining can learn in-context reinforcement learning.

ICLR: In-Context Learning of Representations Supervised pretraining can learn in-context reinforcement learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.830563Z

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Observation c66b1053-f746-49db-a85f-be5c297fae9d · outbound

This paper cites Implicit Representations of Meaning in Neural Language Models.

ICLR: In-Context Learning of Representations Implicit Representations of Meaning in Neural Language Models

Reference 35

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Observation ddd9931e-7124-4171-9b76-abbb1066cbf7 · outbound

This paper cites Emergent world representations: Exploring a sequence model trained on a synthetic task.

ICLR: In-Context Learning of Representations Emergent world representations: Exploring a sequence model trained on a synthetic task

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.811286Z

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Observation dd8d414e-7691-4dad-898d-bc9c1c2965a3 · outbound

This paper cites Emergent world representations: Exploring a sequence model trained on a synthetic task.

ICLR: In-Context Learning of Representations Emergent world representations: Exploring a sequence model trained on a synthetic task

Reference 37

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Observation 498f728d-cdfa-4f00-80e3-03141e9b32e0 · outbound

This paper cites Inference-time intervention: Eliciting truthful answers from a language model.

ICLR: In-Context Learning of Representations Inference-time intervention: Eliciting truthful answers from a language model

Reference 38

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Observation a2bf6d93-532f-481f-8258-3e94ef94436c · outbound

This paper cites In-Context Learning with Many Demonstration Examples.

ICLR: In-Context Learning of Representations In-Context Learning with Many Demonstration Examples

Reference 39

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Observation 6d58a7dd-489c-4d65-9e50-19c8cf1607bf · outbound

This paper cites Transformers Learn Shortcuts to Automata.

ICLR: In-Context Learning of Representations Transformers Learn Shortcuts to Automata

Reference 40

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Observation dc5b4726-7e73-4949-856b-2aaabd30880f · outbound

This paper cites Towards understanding grokking: An effective theory of representation learning.

ICLR: In-Context Learning of Representations Towards understanding grokking: An effective theory of representation learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.781927Z

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Observation 90469e54-1b0b-43c3-9507-e8af4c175e45 · outbound

This paper cites Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity.

ICLR: In-Context Learning of Representations Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.550983Z

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Observation c8d309ed-12df-4c86-aab6-c5f794b39d37 · outbound

This paper cites Mechanistic mode connectivity.

ICLR: In-Context Learning of Representations Mechanistic mode connectivity

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.768836Z

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Observation 03a0ae8c-d464-4755-a367-d8cfa3d4dda7 · outbound

This paper cites A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language.

ICLR: In-Context Learning of Representations A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.558461Z

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Observation 2104c868-97cf-43c4-9972-7a33cec56a89 · outbound

This paper cites Transferring structural knowledge across cognitive maps in humans and models.

ICLR: In-Context Learning of Representations Transferring structural knowledge across cognitive maps in humans and models

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.756610Z

Source-reported events for the cited work

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Observation 15581811-b04f-40f5-98a4-7f0affca2d26 · outbound

This paper cites Flexible neural representations of abstract structural knowledge in the human entorhinal cortex.

ICLR: In-Context Learning of Representations Flexible neural representations of abstract structural knowledge in the human entorhinal cortex

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.745367Z

Source-reported events for the cited work

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Observation baca784e-295a-4b61-9e21-3380fd913d0c · outbound

This paper cites The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets.

ICLR: In-Context Learning of Representations The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Reference 47

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Observation 327763a6-7811-4699-8fab-c23aff650686 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

ICLR: In-Context Learning of Representations Efficient Estimation of Word Representations in Vector Space

Reference 48

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This paper cites Emergent Linear Representations in World Models of Self-Supervised Sequence Models.

ICLR: In-Context Learning of Representations Emergent Linear Representations in World Models of Self-Supervised Sequence Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.580066Z

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Observation baf6e8ba-f03a-4fcd-bd5b-e91d904c6358 · outbound

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ICLR: In-Context Learning of Representations Unresolved cited work

Reference 50

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Observation 9c765ef4-7b8c-4180-a474-37a0ee1ee9ac · outbound

This paper cites Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing.

ICLR: In-Context Learning of Representations Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.587939Z

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Observation b4660bde-2f18-4977-b38a-c5857dbb9571 · outbound

This paper cites Competition Dynamics Shape Algorithmic Phases of In-Context Learning.

ICLR: In-Context Learning of Representations Competition Dynamics Shape Algorithmic Phases of In-Context Learning

Reference 52

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Observation f4ae1e6c-7ed6-44cc-a883-3e9191d5b35c · outbound

This paper cites Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space.

ICLR: In-Context Learning of Representations Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.595778Z

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Observation 9903204b-44bb-4b4e-b1cf-fefdbdb333fa · outbound

This paper cites The Geometry of Categorical and Hierarchical Concepts in Large Language Models.

ICLR: In-Context Learning of Representations The Geometry of Categorical and Hierarchical Concepts in Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.599539Z

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Observation 52423ccb-e417-4de4-915c-1aaa5bcdb45f · outbound

This paper cites The Linear Representation Hypothesis and the Geometry of Large Language Models.

ICLR: In-Context Learning of Representations The Linear Representation Hypothesis and the Geometry of Large Language Models

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.604482Z

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Observation 54d5339a-be2c-4d0e-8381-f4d07873f2ca · outbound

This paper cites Mapping language models to grounded conceptual spaces.

ICLR: In-Context Learning of Representations Mapping language models to grounded conceptual spaces

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.718909Z

Source-reported events for the cited work

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Observation edb3a078-0e03-469c-9731-796d37115518 · outbound

This paper cites Glove: Global vectors for word representation.

ICLR: In-Context Learning of Representations Glove: Global vectors for word representation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.702408Z

Source-reported events for the cited work

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Observation ac9d7667-5d63-465a-b286-07d0ed023f6c · outbound

This paper cites Why think step by step? reasoning emerges from the locality of experience.

ICLR: In-Context Learning of Representations Why think step by step? reasoning emerges from the locality of experience

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.688819Z

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Observation af160166-814f-4c74-9ede-453aa5b877e6 · outbound

This paper cites Sometimes i am a tree: Data drives unstable hierarchical generalization.

ICLR: In-Context Learning of Representations Sometimes i am a tree: Data drives unstable hierarchical generalization

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.622154Z

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Observation 09b08f8a-1e59-4cdb-8b2a-202d25e6c9c8 · outbound

This paper cites Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks.

ICLR: In-Context Learning of Representations Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.625863Z

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Observation ab4ae75b-2feb-426a-b2e3-e8f28eebf36f · outbound

This paper cites Steering llama 2 via contrastive activation addition.

ICLR: In-Context Learning of Representations Steering llama 2 via contrastive activation addition

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.630158Z

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Observation cce515d6-fe17-43d5-b813-c203f0e91a31 · outbound

This paper cites Transformers represent belief state geometry in their residual stream.

ICLR: In-Context Learning of Representations Transformers represent belief state geometry in their residual stream

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.634831Z

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Observation 0e948ccd-847e-4730-8604-f3d8e9fc0903 · outbound

This paper cites Spectral and algebraic graph theory.

ICLR: In-Context Learning of Representations Spectral and algebraic graph theory

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.674005Z

Source-reported events for the cited work

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Observation ab3416d7-3f5d-4845-b3c2-c7cf5f826e0a · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

ICLR: In-Context Learning of Representations Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.643483Z

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Observation ff2fc2c7-4335-49f0-9f1e-b826c0cd9530 · outbound

This paper cites Function Vectors in Large Language Models.

ICLR: In-Context Learning of Representations Function Vectors in Large Language Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.647563Z

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Observation e77a0b56-3d9d-4d34-9524-1a15d297fe0c · outbound

This paper cites Can neural networks learn implicit logic from physical reasoning? In The eleventh international conference on learning representations, 2022.

ICLR: In-Context Learning of Representations Can neural networks learn implicit logic from physical reasoning? In The eleventh international conference on learning representations, 2022

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.661566Z

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Observation cb9929fc-033c-42e0-9dde-e5d1a78ce585 · outbound

This paper cites How to draw a graph.

ICLR: In-Context Learning of Representations How to draw a graph

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.646878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1610c978-03b5-4469-843d-a59d72847b7e · outbound

This paper cites Evaluating the World Model Implicit in a Generative Model.

ICLR: In-Context Learning of Representations Evaluating the World Model Implicit in a Generative Model

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.659540Z

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Observation d4d06f4b-2b51-4944-9035-6a9a81ac8914 · outbound

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

ICLR: In-Context Learning of Representations Transformers learn in-context by gradient descent

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.633811Z

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Observation 7968d552-b9cb-4bf2-bb96-45e1e6e77504 · outbound

This paper cites Uncovering mesa-optimization algorithms in Transformers.

ICLR: In-Context Learning of Representations Uncovering mesa-optimization algorithms in Transformers

Reference 70

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Observation 543dd19f-5e16-47bd-b216-4abc2d532da5 · outbound

This paper cites Emergent Abilities of Large Language Models.

ICLR: In-Context Learning of Representations Emergent Abilities of Large Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.672477Z

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Observation 6b048d21-5333-41fb-b7ef-0d0b90a77af8 · outbound

This paper cites Transformers are uninterpretable with myopic methods: a case study with bounded dyck grammars.

ICLR: In-Context Learning of Representations Transformers are uninterpretable with myopic methods: a case study with bounded dyck grammars

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.621667Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a21f3a35-9eee-483f-bcdf-b82588d23b28 · outbound

This paper cites The tolman-eichenbaum machine: unifying space and relational memory through generalization in the hippocampal formation.

ICLR: In-Context Learning of Representations The tolman-eichenbaum machine: unifying space and relational memory through generalization in the hippocampal formation

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.608333Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ad3ab82a-4e86-49aa-af09-9633a3ca7a16 · outbound

This paper cites Transformers from an optimization perspective.

ICLR: In-Context Learning of Representations Transformers from an optimization perspective

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:24:02.595009Z

Source-reported events for the cited work

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Observation 3d599de6-ce4b-4234-8735-d37525f184ff · outbound

This paper cites write newline.

ICLR: In-Context Learning of Representations write newline

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.687218Z

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Observation 33905bfe-3208-46bb-a715-79376da362c0 · outbound

This paper cites @esa (Ref.

ICLR: In-Context Learning of Representations @esa (Ref

Reference 76

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Observation 182b45f7-a037-4048-b21b-e2ccecf3f64b · outbound

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ICLR: In-Context Learning of Representations Unresolved cited work

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.697079Z

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Observation ab2c5af7-a986-44ce-ad64-38c6bb073fa5 · outbound

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ICLR: In-Context Learning of Representations Unresolved cited work

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-10T23:24:01.701539Z

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Pith citing papers

Observation b53388a2-3ccf-4462-b05b-63196849e882 · inbound

Harmonic Loss Trains Interpretable AI Models cites this paper.

Harmonic Loss Trains Interpretable AI Models ICLR: In-Context Learning of Representations

Reference 19

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Observation fee1d4d4-a77b-4914-9591-779585ae5ef3 · inbound

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs cites this paper.

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs ICLR: In-Context Learning of Representations

Reference 44

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Observation fdb4c33e-d39a-4ca7-875c-f4926456ee38 · inbound

A Survey of Scaling in Large Language Model Reasoning cites this paper.

A Survey of Scaling in Large Language Model Reasoning ICLR: In-Context Learning of Representations

Reference 152

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Observation d3d6ecd3-ceff-424c-88bd-5cb7f759430a · inbound

On Entity Identification in Language Models cites this paper.

On Entity Identification in Language Models ICLR: In-Context Learning of Representations

Reference 2013

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Observation cbb59033-0b0e-47da-a17c-3453b7beacaf · inbound

Provable Low-Frequency Bias of In-Context Learning of Representations cites this paper.

Provable Low-Frequency Bias of In-Context Learning of Representations ICLR: In-Context Learning of Representations

Reference 13

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Observation e0ac701d-b4a0-4f9b-a380-65175412effb · inbound

A Markov Categorical Framework for Language Modeling cites this paper.

A Markov Categorical Framework for Language Modeling ICLR: In-Context Learning of Representations

Reference 23

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Observation 0934223d-ea0f-42ea-b9f9-43dd36198e80 · inbound

ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement cites this paper.

ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement ICLR: In-Context Learning of Representations

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:06:05.002199Z

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Observation 67a62d91-c067-4665-97eb-002fe41e0563 · inbound

A framework for analyzing concept representations in neural models cites this paper.

A framework for analyzing concept representations in neural models ICLR: In-Context Learning of Representations

Reference 172

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Observation 689aa3bb-4778-4f13-9d7f-a1543783fed9 · inbound

Uncovering and Shaping the Latent Representation of 3D Scene Topology in Vision-Language Models cites this paper.

Uncovering and Shaping the Latent Representation of 3D Scene Topology in Vision-Language Models ICLR: In-Context Learning of Representations

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:00:55.026979Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1ff63002-bf84-41ac-b4ce-1920cc4cf796 · inbound

Belief or Circuitry? Causal Evidence for In-Context Graph Learning cites this paper.

Belief or Circuitry? Causal Evidence for In-Context Graph Learning ICLR: In-Context Learning of Representations

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:41:23.966886Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 893d285e-9c96-4949-853d-b2c56c178cc3 · inbound

Yang-Mills-Higgs: A Geometric Theory of Binary Labels on Non-Contractible Spaces cites this paper.

Yang-Mills-Higgs: A Geometric Theory of Binary Labels on Non-Contractible Spaces ICLR: In-Context Learning of Representations

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:06:40.546568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7d93e54b-1075-4f79-b895-bd09716d3342 · inbound

Context Is King: How In-Context Specification Shapes the Geometry of Concepts cites this paper.

Context Is King: How In-Context Specification Shapes the Geometry of Concepts ICLR: In-Context Learning of Representations

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.