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Paper Citation Record · LEDGER

Towards Compute-Optimal Many-Shot In-Context Learning

As of 7 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.16217.

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

pith.paper-citation-record.v1
2507.16217 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:20:38.759814Z

measured 43 of 43 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy10
  • unresolved29
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e5e89fd3-20cc-4642-b088-769d17eb2978 · outbound

This paper cites Many-Shot In-Context Learning.

Towards Compute-Optimal Many-Shot In-Context Learning Many-Shot In-Context Learning

Reference 1

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Observation 4260c449-f816-497e-ab0f-7f3958d2a966 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Towards Compute-Optimal Many-Shot In-Context Learning Gemini: A Family of Highly Capable Multimodal Models

Reference 3

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Observation 7bbeede1-aceb-4780-bf81-11f250e6d22c · outbound

This paper cites In-Context Learning with Long-Context Models: An In-Depth Exploration.

Towards Compute-Optimal Many-Shot In-Context Learning In-Context Learning with Long-Context Models: An In-Depth Exploration

Reference 5

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Observation 91197974-bb70-419e-a4fa-fbb1f1e7438a · outbound

This paper cites impact of sample selection on in-context learning for entity extraction from scientific writing.

Towards Compute-Optimal Many-Shot In-Context Learning impact of sample selection on in-context learning for entity extraction from scientific writing

Reference 6

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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.

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Observation 29bf1371-ae60-49f6-bca4-c790bdedfca5 · outbound

This paper cites doi: 10.18653/v1/2023.findings-emnlp.338.

Towards Compute-Optimal Many-Shot In-Context Learning doi: 10.18653/v1/2023.findings-emnlp.338

Reference 7

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Observation e91cdd25-7fa1-4323-949b-6a977d22db21 · outbound

This paper cites Papailiopoulos, and Kangwook Lee.

Towards Compute-Optimal Many-Shot In-Context Learning Papailiopoulos, and Kangwook Lee

Reference 9

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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.

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Observation 6089dcf4-55b7-4407-a7b9-99669a33a215 · outbound

This paper cites Data Engineering for Scaling Language Models to 128K Context.

Towards Compute-Optimal Many-Shot In-Context Learning Data Engineering for Scaling Language Models to 128K Context

Reference 11

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Observation 29e7bc85-96b5-4e8d-98f4-d4321f4b82bc · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Towards Compute-Optimal Many-Shot In-Context Learning Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 12

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Observation 4944664d-a834-4a4f-8659-fc32c73a031a · outbound

This paper cites Time travel in llms: Tracing data contamina- tion in large language models.

Towards Compute-Optimal Many-Shot In-Context Learning Time travel in llms: Tracing data contamina- tion in large language models

Reference 13

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source=pdf_text observed=2026-08-06T15:20:38.636179Z digest=sha256:e5901dec9e97fb5ed2ac9892ca8fd1c5bde4d2fea605013105ed2febb9bdfd52

Observation e803960a-142f-48d5-b84e-bf3718edcfcd · outbound

This paper cites Memorization in In-Context Learning.

Towards Compute-Optimal Many-Shot In-Context Learning Memorization in In-Context Learning

Reference 14

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Observation 9611d3c9-7e26-4b39-9233-d0419d37f5eb · outbound

This paper cites Structured Prompting: Scaling In-Context Learning to 1,000 Examples.

Towards Compute-Optimal Many-Shot In-Context Learning Structured Prompting: Scaling In-Context Learning to 1,000 Examples

Reference 16

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Observation 9cb024c4-16b0-4950-b111-3ee26af8895f · outbound

This paper cites In-Context Learning Creates Task Vectors.

Towards Compute-Optimal Many-Shot In-Context Learning In-Context Learning Creates Task Vectors

Reference 17

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Observation 95eb9f2f-dd60-4303-995a-fb97ec87b6d8 · outbound

This paper cites Many-Shot In-Context Learning in Multimodal Foundation Models.

Towards Compute-Optimal Many-Shot In-Context Learning Many-Shot In-Context Learning in Multimodal Foundation Models

Reference 19

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Observation 6f8215d5-9b8f-48d8-ac21-8d5d05745e2b · outbound

This paper cites In-Context Learning Learns Label Relationships but Is Not Conventional Learning.

Towards Compute-Optimal Many-Shot In-Context Learning In-Context Learning Learns Label Relationships but Is Not Conventional Learning

Reference 20

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Observation 2019cac0-bec2-4ea6-bd9d-013e0c9b7373 · outbound

This paper cites Gecko: Versatile Text Embeddings Distilled from Large Language Models.

Towards Compute-Optimal Many-Shot In-Context Learning Gecko: Versatile Text Embeddings Distilled from Large Language Models

Reference 21

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Observation 2b114263-aba0-4e37-ab0b-864fca969c3f · outbound

This paper cites LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods.

Towards Compute-Optimal Many-Shot In-Context Learning LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods

Reference 22

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Observation a39f48aa-7098-48ac-b5e3-ade49e8e8822 · outbound

This paper cites What Makes Good In-Context Examples for GPT-$3$?.

Towards Compute-Optimal Many-Shot In-Context Learning What Makes Good In-Context Examples for GPT-$3$?

Reference 24

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Observation 586da89a-99a3-4d85-8d54-97db4c097fdb · outbound

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

Towards Compute-Optimal Many-Shot In-Context Learning Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 26

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Observation 2fca83ba-a507-464d-9217-3e2b7e203370 · outbound

This paper cites Many-Shot In-Context Learning for Molecular Inverse Design.

Towards Compute-Optimal Many-Shot In-Context Learning Many-Shot In-Context Learning for Molecular Inverse Design

Reference 27

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Observation 0d26c430-9e59-42db-a2c5-8ede77ffc4e5 · outbound

This paper cites Adversarial NLI: A New Benchmark for Natural Language Understanding.

Towards Compute-Optimal Many-Shot In-Context Learning Adversarial NLI: A New Benchmark for Natural Language Understanding

Reference 28

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Observation ee487ebb-ba47-43cb-bd0a-477afc8b3e92 · outbound

This paper cites Can many-shot in-context learning help llms as evaluators? A preliminary empirical study.

Towards Compute-Optimal Many-Shot In-Context Learning Can many-shot in-context learning help llms as evaluators? A preliminary empirical study

Reference 29

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

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Observation ae2eafa4-3769-4ce6-9239-dd9d038479b5 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Towards Compute-Optimal Many-Shot In-Context Learning Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 30

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Observation 68826746-899d-487a-be83-c61eca0d80c2 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Towards Compute-Optimal Many-Shot In-Context Learning Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 32

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Observation 55544b3e-6047-4f8a-823e-e2745b3b2604 · outbound

This paper cites Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization.

Towards Compute-Optimal Many-Shot In-Context Learning Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization

Reference 34

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Observation c993669c-f7b4-4e3f-b7ec-005ed0ee6eb1 · outbound

This paper cites From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation.

Towards Compute-Optimal Many-Shot In-Context Learning From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation

Reference 35

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Observation 32fb9a7a-cbf1-44e8-8f1d-9d213e3fc7df · outbound

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

Towards Compute-Optimal Many-Shot In-Context Learning Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations

Reference 36

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Observation 5fa91c2f-1b3f-41cd-8f40-a19b62036401 · outbound

This paper cites Sentiment Analysis in the Era of Large Language Models: A Reality Check.

Towards Compute-Optimal Many-Shot In-Context Learning Sentiment Analysis in the Era of Large Language Models: A Reality Check

Reference 37

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Observation bffd6898-4e0f-4945-a8ea-57a087bd2866 · outbound

This paper cites Active Example Selection for In-Context Learning.

Towards Compute-Optimal Many-Shot In-Context Learning Active Example Selection for In-Context Learning

Reference 38

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Observation 638c4bec-d0a6-4923-8012-eb74b9cdc59e · outbound

This paper cites Calibrate before use: Improving few-shot performance of language models.

Towards Compute-Optimal Many-Shot In-Context Learning Calibrate before use: Improving few-shot performance of language models

Reference 39

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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.

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Observation 22d02d1d-3d86-42eb-b700-5c81082efe2a · outbound

This paper cites an unresolved cited work.

Towards Compute-Optimal Many-Shot In-Context Learning Unresolved cited work

Reference 40

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

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Observation 74dd82a6-c71b-478f-8116-79edc173a882 · outbound

This paper cites This portion of the prompt is updated for each downstream test sample.

Towards Compute-Optimal Many-Shot In-Context Learning This portion of the prompt is updated for each downstream test sample

Reference 42

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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=2026-08-06T15:20:38.755614Z digest=sha256:0c9ae2cd27d68d724569775ca2b509d3e5dd40d589e50d703baf0cdba8622316

Observation c6367907-95b8-43e3-8eae-ccdbdee0014a · outbound

This paper cites From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples.

Towards Compute-Optimal Many-Shot In-Context Learning From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples

Reference 1953

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local_arxiv, observed 2026-08-06T15:20:38.896069Z

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=2026-08-06T15:20:38.711643Z digest=sha256:7e6451b05dd5818faf505856f47c6d6aab2b84bfcfab793ceff6d74a1477ea60

Observation 614594c2-3630-4643-a80d-70827129b7fd · outbound

This paper cites an unresolved cited work.

Towards Compute-Optimal Many-Shot In-Context Learning Unresolved cited work

Reference 1991

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raw_fallback, observed 2026-08-06T15:20:39.267622Z

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

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Observation 22550fcd-f160-4d2f-bbd9-269ad5bc33d1 · outbound

This paper cites MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use.

Towards Compute-Optimal Many-Shot In-Context Learning MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use

Reference 2001

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source=pdf_text observed=2026-08-06T15:20:38.656905Z digest=sha256:a921de837dc46248f2f81dbba15f7195ec7c4cea5826d280fff674c910385e69

Observation 82843581-f3b9-4302-b1a0-e522df749fc8 · outbound

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

Towards Compute-Optimal Many-Shot In-Context Learning Dual Operating Modes of In-Context Learning

Reference 2002

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local_arxiv, observed 2026-08-06T15:20:38.997554Z

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=2026-08-06T15:20:38.677270Z digest=sha256:5903b73ee52e594e36b69fe60eebb20eacf8a61a8aa61fb0204ad6bb09cc304b

Observation 66d6077e-d40b-4279-9a62-5657fab0871e · outbound

This paper cites That error will be one of the following types: Named Entities: An entity (names, places, locations, etc.) is changed to a different entity.

Towards Compute-Optimal Many-Shot In-Context Learning That error will be one of the following types: Named Entities: An entity (names, places, locations, etc.) is changed to a different entity

Reference 2015

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raw_fallback, observed 2026-08-06T15:20:39.240685Z

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=2026-08-06T15:20:38.759814Z digest=sha256:e72b065faf4cf9bb775814de8888dcf2d932118edb26f8a985489ad353d83ad8

Observation be1332f3-9f33-48a5-8a39-7b5e3d826302 · outbound

This paper cites Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, Jo ˜ao Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, and Max Vladymyrov.

Towards Compute-Optimal Many-Shot In-Context Learning Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, Jo ˜ao Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, and Max Vladymyrov

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:39.311194Z

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=2026-08-06T15:20:38.719460Z digest=sha256:565d57ca6dc66a1bafba3a8e2824235fb601cea934a4d39fdb1f1a25d0c52b28

Observation 93e6196b-4e58-4f7d-9496-740392bcb826 · outbound

This paper cites LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.

Towards Compute-Optimal Many-Shot In-Context Learning LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:38.582379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:20:38.582379Z digest=sha256:aa2551cfc77e0ae9b2033086b88e2dfa9f176f1152a3d30192c29e87d319d20b

Observation 346b5bb3-711d-48d8-8423-0d7143312ac8 · outbound

This paper cites Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity.

Towards Compute-Optimal Many-Shot In-Context Learning Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:38.685258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:20:38.685258Z digest=sha256:17931431421659915d20f2adf43f2e248bb3ee8890b87306dfd7887c82692c02

Observation 9cb5e1ab-f374-4131-9d28-70fbe4026869 · outbound

This paper cites A Survey on In-context Learning.

Towards Compute-Optimal Many-Shot In-Context Learning A Survey on In-context Learning

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:38.621661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:20:38.621661Z digest=sha256:183eaf0372d46cf581017f5c6b98370bc35829c87e11589fee6442de38d9efed

Observation ca0bdf73-0943-45c6-925d-1c0d4af84acd · outbound

This paper cites Revisiting In-Context Learning with Long Context Language Models.

Towards Compute-Optimal Many-Shot In-Context Learning Revisiting In-Context Learning with Long Context Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:38.184876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:20:38.184876Z digest=sha256:bc29fed121f4ac2ae52acaf7a14dd9e27417a2864c4932d306a817507027d4bd

Observation 456f5d0c-4ed0-4080-8f6c-4114818587dd · outbound

This paper cites How Do In-Context Examples Affect Compositional Generalization?.

Towards Compute-Optimal Many-Shot In-Context Learning How Do In-Context Examples Affect Compositional Generalization?

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:38.084083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:20:38.084083Z digest=sha256:18b7e12a028416fee5824987da28b785f72434d44aa5c45167d1b952329e626c

Observation 72d0d03b-efb0-40e1-91c3-d98a02f68f2d · outbound

This paper cites Accessed: 2025-02-13.

Towards Compute-Optimal Many-Shot In-Context Learning Accessed: 2025-02-13

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:20:39.356892Z

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=2026-08-06T15:20:38.644765Z digest=sha256:db3dce67602d80c6298671a43198ce9294733fed6526d5acf613ef4ac22263c5

Pith citing papers

No inbound Pith citation observations are available.