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Paper Citation Record · LEDGER

Incomplete In-context Learning

As of 18 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 4 inbound Pith citation observations for arXiv:2505.07251.

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

pith.paper-citation-record.v1
2505.07251 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:24:59.716448Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T16:16:22.897866Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T10:24:21.464641Z

Reference resolution

48 of 48 outbound references displayed

  • verified exact1
  • verified fuzzy28
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 597c116e-4546-419d-868b-3b759035b806 · outbound

This paper cites Cifar-10: Knn-based ensemble of classifiers.

Incomplete In-context Learning Cifar-10: Knn-based ensemble of classifiers

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.501126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.512365Z digest=sha256:edfcf460acd2b4861f30ef8341caed79fde9f1f675aa0419efaa75714ac175c4

Observation 27e6451e-f175-4640-8f2e-a7c4fe457e54 · outbound

This paper cites Handling extreme class imbal- ance in technical logbook datasets.

Incomplete In-context Learning Handling extreme class imbal- ance in technical logbook datasets

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.481070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.518145Z digest=sha256:b558c593c7ddbabc4cc2bb5036c7c6be522824536770db8238e736ba344c08f4

Observation 682e501f-120e-418b-a9af-175bbd24cdad · outbound

This paper cites Why label when you can search? alternatives to active learning for applying human resources to build classification models under extreme class imbalance.

Incomplete In-context Learning Why label when you can search? alternatives to active learning for applying human resources to build classification models under extreme class imbalance

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.462332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.522698Z digest=sha256:e107d0089e0a9b93578d55e91cae980310acd3baf24b21de2ab42ebc83c9dd25

Observation 911b8709-57f0-4e72-8a62-933285b40a34 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020.

Incomplete In-context Learning Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.444356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.527562Z digest=sha256:39f413a6da455631daf09a5d3124a7318c331a4e8ed4544fe1fc2e8623b882be

Observation 2aefb74e-5d24-4452-b517-ccabf4919a7a · outbound

This paper cites an unresolved cited work.

Incomplete In-context Learning Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-15T22:25:00.426633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.533324Z digest=sha256:09030219132f40dac19f07d2c42d31dca8e6733d5f043790d137d7435f5291b9

Observation 91da7573-2b51-4f90-ba4f-b793ef64e51d · outbound

This paper cites Class incremental learning for image classification with out- of-distribution task identification.IEEE Transactions on Mul- timedia, 2025.

Incomplete In-context Learning Class incremental learning for image classification with out- of-distribution task identification.IEEE Transactions on Mul- timedia, 2025

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.413537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.537923Z digest=sha256:65eea4845d054f4b6957e4fadd4cef430b582865b4f2e661002c326e3f0e547b

Observation dfc3a5c9-9871-447b-b2c9-cbd3b18667bf · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Incomplete In-context Learning Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.542651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.542651Z digest=sha256:fded86bf3d74d2bbf27152418b71b645afe14f53e60060711a817dfb37374ab3

Observation 12e1a943-16fb-4ca7-9c9f-ae092eff4b47 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

Incomplete In-context Learning Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.547200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.547200Z digest=sha256:d5273e1c8598e3ff0350cda4950d0e3ff090109e1d88d36c1ff18709773cc9a7

Observation c7b5c7ad-628d-415b-a94c-b48b0e7e67c8 · outbound

This paper cites Exploring the Robustness of In-Context Learning with Noisy Labels.

Incomplete In-context Learning Exploring the Robustness of In-Context Learning with Noisy Labels

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:24:59.846941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.551948Z digest=sha256:15058fe4dd0b8adeb4b2582b5fba7eff5110ebd3c006ca1c2ce10d4a97342334

Observation 8a174988-350d-4fe3-a09b-af28ead73259 · outbound

This paper cites Meta-in-context learning in large language models.Advances in Neural Infor- mation Processing Systems, 36:65189–65201, 2023.

Incomplete In-context Learning Meta-in-context learning in large language models.Advances in Neural Infor- mation Processing Systems, 36:65189–65201, 2023

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.390572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.556252Z digest=sha256:a472d8a0c7e01eb1c51130a450437f28f92c9b057501ddf8cf0a2a9542b4fd1e

Observation f03f847f-dea8-4680-99a9-7d8fdc14f870 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Incomplete In-context Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.374804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.560287Z digest=sha256:525d6a155c369e4c0c03a61cd52fe990403d0659e16d594f6176cdab7c588f56

Observation 3b7ee574-bf89-4e38-8f0b-1b160b474d52 · outbound

This paper cites Mit- igating label biases for in-context learning.

Incomplete In-context Learning Mit- igating label biases for in-context learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.356646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.564431Z digest=sha256:12cd2a9a97306e0096f43715f15cb428a6b48f484a08690e6f2d396de37bc1a8

Observation 0da746ec-6f9b-4db7-afa4-a23b8042c1a8 · outbound

This paper cites Complexity-based prompting for multi-step reasoning.

Incomplete In-context Learning Complexity-based prompting for multi-step reasoning

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.339393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.568351Z digest=sha256:4cb23e9d6617040240e6e296283cfa547d4e6ea5ed5100049bdc990da1caad9c

Observation 2b8ecec0-4c65-46ca-9806-e2f368953470 · outbound

This paper cites Demystifying prompts in language models via perplexity estimation.

Incomplete In-context Learning Demystifying prompts in language models via perplexity estimation

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.324514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.572312Z digest=sha256:f7b1afbc3508a2264fa04fbd7e5fa601ea5ae8550af9f825305972878eca6144

Observation 26cd35f1-ff27-4fe3-9998-4d6e690351fe · outbound

This paper cites How Robust are LLMs to In-Context Majority Label Bias?.

Incomplete In-context Learning How Robust are LLMs to In-Context Majority Label Bias?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.576587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.576587Z digest=sha256:4cc4b2f6e55c50340c0745e00142b52936f6a288b006734cdd6440d5e2136b20

Observation 48bee1ae-367e-4eed-95c9-3e1bb2ee82e5 · outbound

This paper cites Coverage- based example selection for in-context learning.

Incomplete In-context Learning Coverage- based example selection for in-context learning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.307849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.580991Z digest=sha256:3e2d6bb7118c5b532ce9a62d5263fc0e4af736714649b60959ba41511d9a1c60

Observation 95b8a870-5220-4e68-b7c8-893e71d0336d · outbound

This paper cites In-context learning learns label relationships but is not conventional learning.

Incomplete In-context Learning In-context learning learns label relationships but is not conventional learning

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.290393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.584994Z digest=sha256:0dc4ffc77a6892c7b9d4a18154ac045f495274c7a8ae4bbca3fabd0e723dc076

Observation b117614f-d14f-43bf-9862-4c41164e2749 · outbound

This paper cites Learning multiple layers of features from tiny images.

Incomplete In-context Learning Learning multiple layers of features from tiny images

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.589031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.589031Z digest=sha256:2cbda243a8da4bb6076903a7590096163482ca2f2365a823dba49486ca5ceb59

Observation 72c02d9c-074b-47ef-a60c-25663eb455fd · outbound

This paper cites Prompt-based concept learning for few-shot class-incremental learning.IEEE Transactions on Circuits and Systems for Video Technology, 2025.

Incomplete In-context Learning Prompt-based concept learning for few-shot class-incremental learning.IEEE Transactions on Circuits and Systems for Video Technology, 2025

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.259962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.592669Z digest=sha256:6bf0a54129dbe9f7925e5aa8cec4612c2bcb33a658a485c19dccab7e6d41f501

Observation 2062bd19-13a0-4365-93f7-e25a5f91320d · outbound

This paper cites Finding support examples for in- context learning.

Incomplete In-context Learning Finding support examples for in- context learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.231109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.596776Z digest=sha256:aff786fd1e47a8d330a76be09208feb76b1639dacc3fad7d7471461d52d05b3a

Observation 7bcf0c1e-b270-4792-bf58-86329f1c6520 · outbound

This paper cites Mot: Pre-thinking and recall- ing enable chatgpt to self-improve with memory-of-thoughts.

Incomplete In-context Learning Mot: Pre-thinking and recall- ing enable chatgpt to self-improve with memory-of-thoughts

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.209788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.600868Z digest=sha256:0c9c1f64047f06d1f48ddde4bf66f660980519737b88cc86a220b9470b7bfb3a

Observation 941ede49-54db-45b8-b431-baff451d742b · outbound

This paper cites an unresolved cited work.

Incomplete In-context Learning Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-15T22:25:00.192276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.604998Z digest=sha256:0ae025703ab706586fd3cd01391b93d15b5e88aa5269cd09f75bdfde5af2dffd

Observation 0884c381-4823-4ebe-b7fe-72ecc98bf164 · outbound

This paper cites Class incremental learning with self-supervised pre-training and prototype learning.Pattern Recognition, 157:110943, 2025.

Incomplete In-context Learning Class incremental learning with self-supervised pre-training and prototype learning.Pattern Recognition, 157:110943, 2025

Reference 23

Resolution
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no resolver link, observed 2026-08-15T22:24:59.608809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.608809Z digest=sha256:809cb62503f357af59333118ad32776136c956d92fcd6b6b759d3b708870056c

Observation c3728138-18b0-468d-9ad6-11084ab14046 · outbound

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

Incomplete In-context Learning Does In-Context Learning Really Learn? Rethinking How Large Language Models Respond and Solve Tasks via In-Context Learning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.613022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.613022Z digest=sha256:c4dd0bc640aa54f8bcf2ab81dd1ffa73a6870885eaf9bb29527546e11de32b57

Observation 8cb81720-6142-4ece-a4e0-ae0888f2bf80 · outbound

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

Incomplete In-context Learning Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.617780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.617780Z digest=sha256:c8ca1c985f489765dde452b2eb2000b827a14c6849066f6cb3b108dbbfb1ebf4

Observation bc42c7f3-9c86-4d15-81e2-e818c5e2fe4d · outbound

This paper cites Z-ICL: Zero-shot in-context learning with pseudo-demonstrations.

Incomplete In-context Learning Z-ICL: Zero-shot in-context learning with pseudo-demonstrations

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.148989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.621714Z digest=sha256:9ae5a2d680dd62643801d2881d0614850e29c48c77f72059cd046bbcf32b2fbc

Observation 05f0a30a-4984-441d-83ab-3afffa52305b · outbound

This paper cites Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection.

Incomplete In-context Learning Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.625516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.625516Z digest=sha256:91121d65c4d6581e4c6b9c662eb9b28ab025b68377fc4b22524650bcab254459

Observation 692d33fb-c678-4ca1-b80a-0064f3dd6f67 · outbound

This paper cites In- context learning for text classification with many labels.

Incomplete In-context Learning In- context learning for text classification with many labels

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.128562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.630301Z digest=sha256:9b511fe468a5560c4ff0aca199be67e6b067e7803b0d68333bcb79933a8c3fd3

Observation 3e6c7129-2354-4c3b-a1ae-cf0df61ee5ca · outbound

This paper cites MetaICL: Learning to learn in context.

Incomplete In-context Learning MetaICL: Learning to learn in context

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.108786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.634219Z digest=sha256:84a3e5488fa8fea372b3f886bf012237483a7b04af96083a18308439df10b6cd

Observation 9bb54492-e368-4b0d-a5cc-2c081bfed8d2 · outbound

This paper cites an unresolved cited work.

Incomplete In-context Learning Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-15T22:25:00.089412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.639220Z digest=sha256:2b7e67918134b6c87a2ef7ad4a912c59124ffc0817af1c12b35986572d0aa407

Observation f03c1c6a-0acc-4431-ba64-48b39af256ca · outbound

This paper cites Diversity of thought improves reasoning abilities of large language models.

Incomplete In-context Learning Diversity of thought improves reasoning abilities of large language models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.070441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.643802Z digest=sha256:1400206fc9fd2fd816a9bcd6da1d658c298fc1189be80e2843de23c7540d7eda

Observation b9c681cc-c2ec-45ae-85f3-6745c415d28e · outbound

This paper cites Improving language understanding by gener- ative pre-training.

Incomplete In-context Learning Improving language understanding by gener- ative pre-training

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.647956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.647956Z digest=sha256:3251ae555b5e31602bf154de5b968341c316308afffef4e465de6993a23b102e

Observation 76326bfe-21b1-4d2d-9994-3d1826c00be5 · outbound

This paper cites Language models are unsuper- vised multitask learners.OpenAI blog, 1(8):9, 2019.

Incomplete In-context Learning Language models are unsuper- vised multitask learners.OpenAI blog, 1(8):9, 2019

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.034653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.652321Z digest=sha256:95a00c19e0c5a1ae31bc6f3ecafc2712d37fe90b22697878d65daf2802bc30cf

Observation 4b65addf-672e-497e-a3fd-516b4ba18c9b · outbound

This paper cites Learning transferable visual models from natural language supervision.

Incomplete In-context Learning Learning transferable visual models from natural language supervision

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:25:00.005125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.656543Z digest=sha256:3c2fc3f140b59f7910caec8c5a33f662e34ffdc401f3f24ab23fce1948f9d31c

Observation 3159a7a6-221f-4908-83f3-0266dbe9779a · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Incomplete In-context Learning Learning transferable visual models from natural language supervi- sion

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.660253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.660253Z digest=sha256:39b55a047a487154cda007c2acd10df573b1758b31fc1afc352e0104427cc3d8

Observation 19c6f671-62d8-44ff-8c42-1345681e7297 · outbound

This paper cites an unresolved cited work.

Incomplete In-context Learning Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-15T22:24:59.982858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.664876Z digest=sha256:108f563c349004cccbb2609cb7568566f1341d1c2742dd64c905297e01365922

Observation 0f783ea6-27db-47c3-accb-090fcc6b1fd2 · outbound

This paper cites Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature.

Incomplete In-context Learning Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.668599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.668599Z digest=sha256:b2927f13cf967bdaf610454d5c73fad7e402b7ed22969dd8255e5b695b53d004

Observation 970eef8e-84b8-4567-8a2b-a838c19d36d3 · outbound

This paper cites Label words are anchors: An information flow perspective for understanding in-context learning.

Incomplete In-context Learning Label words are anchors: An information flow perspective for understanding in-context learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.969467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.673583Z digest=sha256:561e3853c5c4d817bb2a70bcb4ca5845cec5d1f7d3ef520747ec488397af97cb

Observation 916cd7b0-fff0-458b-8cbd-f4262230278d · outbound

This paper cites Large language models are latent variable models: Explaining and finding good demonstrations for in-context learning.

Incomplete In-context Learning Large language models are latent variable models: Explaining and finding good demonstrations for in-context learning

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.956956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.677632Z digest=sha256:f80919a8b9e371da9e8d37ed5463dd08fbf22a36cb2ebcdb39c1166b60ec66b7

Observation 8e083543-98c4-41da-85b2-afe785cd4325 · outbound

This paper cites Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus.

Incomplete In-context Learning Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.944337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.682001Z digest=sha256:2feb7c7118fb1402d74cdc3aca1413ed18959c3a9aa46e3cb4527db2405ac2e8

Observation 10a12eb9-a504-428e-8f5b-3d06998c0634 · outbound

This paper cites Chi, Quoc V.

Incomplete In-context Learning Chi, Quoc V

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.685996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.685996Z digest=sha256:025fa3180aeccd94b3f3a35b283de87bba7f94a2bc45569d7bd1dfe6110dbe53

Observation 2a39cc9c-7fed-4452-92cb-61d92573c9fc · outbound

This paper cites Symbol tuning improves in- context learning in language models.

Incomplete In-context Learning Symbol tuning improves in- context learning in language models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.917812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.690493Z digest=sha256:2a4925700aea886ae7b7856a31a2a6430007c951d23a9ea140e9073f555c2034

Observation 16370a3b-e427-4e7e-acf6-71b03a41b8d8 · outbound

This paper cites Larger language models do in-context learning differently.

Incomplete In-context Learning Larger language models do in-context learning differently

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.694539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.694539Z digest=sha256:311ab0ac259d2b633db2e8a8570a3d4a65e002ca3b93ac3beed4d6096a9caaf5

Observation 15fb0835-d7d1-4abc-a89c-82f2127f7c56 · outbound

This paper cites Self-adaptive in-context learning: An information compression perspective for in-context example selection and ordering.

Incomplete In-context Learning Self-adaptive in-context learning: An information compression perspective for in-context example selection and ordering

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.902755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.698950Z digest=sha256:ceda282303279d23746743ff45a8a3e008a2c7748fb64f2565216ca65151cf48

Observation 43a1dfea-1394-4f7f-8dce-b59160319996 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Incomplete In-context Learning Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.703634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.703634Z digest=sha256:723caf1ec275f6ec2e9b46051c8b55a1742cf3a3447201efe24c5ec629e0362b

Observation faa3a691-89c1-44e9-b595-4cdbce57bccf · outbound

This paper cites Few-shot class-incremental learning for classifi- cation and object detection: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

Incomplete In-context Learning Few-shot class-incremental learning for classifi- cation and object detection: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.889907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.708322Z digest=sha256:81b39d24db34a75018d640ffae3bf887c79538eabf523b7328fe2971cc4bddf0

Observation 1e3ea481-805e-4206-83b0-870d942e3f3b · outbound

This paper cites Towards robust ranker for text retrieval.

Incomplete In-context Learning Towards robust ranker for text retrieval

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:59.874045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T22:24:59.712422Z digest=sha256:f19e0cae586daf3eafb978243d5581b9811b8ca2325415830e3b77629a960b4d

Observation d72af2e4-4f7f-4bcb-b81f-3a340d8485f2 · outbound

This paper cites Visual In-Context Learning for Large Vision-Language Models.

Incomplete In-context Learning Visual In-Context Learning for Large Vision-Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:59.716448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:24:59.716448Z digest=sha256:c83727721b807d2f54e4d76f185752fbd1b258c786cf4bcf7173b84ba03490dd

Pith citing papers

Observation 7274ed97-2981-409b-97c3-fd2c63db3ef9 · inbound

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations cites this paper.

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations Incomplete In-context Learning

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:24:21.466808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T10:21:36.624663Z digest=sha256:96f688ddbab6ffabe6dad7a9e61a4b5bacf8c31b366051b9fb98811822a134ee

Observation 95b14b61-0ea7-4f31-a939-b8d0dc9ae2a3 · inbound

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations cites this paper.

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations Incomplete In-context Learning

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-02T16:15:50.337661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:15:50.337661Z digest=sha256:28fe141f47d01c718595352595c8c7c4063279dab42292649533410b817adca6

Observation ee9d26c4-e3fb-4ad9-a5ba-48566e89c6d4 · inbound

Category-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework cites this paper.

Category-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework Incomplete In-context Learning

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:19:20.115129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T10:17:30.010781Z digest=sha256:a7a04edf1f9eb20fda354b1e358b5f9c90a04c384486fb8d23b00c4b68a1ddef

Observation 6d0d6bdf-3358-4b8f-97d9-e076229c3ccb · inbound

Category-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework cites this paper.

Category-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework Incomplete In-context Learning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-02T16:16:22.897866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:16:22.897866Z digest=sha256:c5a1443df5a1f6a042cc54fb3cbe5f51cfe23bd3675c8de940bce6a0390d41b3