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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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.512365Z digest=sha256:0e270f2af02d22ca80ab9244769e33cef71332e071f67c326a81b7d9eb18623a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.518145Z digest=sha256:50a272936913968e663cf329933771905c3ac0697f5aa0a4d9492335e014e628

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.522698Z digest=sha256:ee83b8183354bd9baac43c50907ee2adff96e5f397920d0a0f6a09ec2b7646e9

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.527562Z digest=sha256:2972104ae6b358ab393fc8b4a638dbf98634c422963a3346ca139085ae54685e

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.533324Z digest=sha256:15594580fe9d48265af872c72754d9c4c85f61957b2a0738edb29c2d37474803

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.537923Z digest=sha256:cfe6c587866e0fb6677d0ec4a125338ea14500c49d7376b5e9faa92b4aef1c09

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:e9d23b8db1f02127ace994eb75c71ea02d6dc2729960363da2bd3beb1ef6d531

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=sha256:651e0ac32c503f9b6f9227c2341e4cfd67870d4eb95b566ef2c531ac84a27320

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.551948Z digest=sha256:e32582e00110c8dda70096d1f9a7b3b3d2843b9d06641b2b7a7641fc9867b3b8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.556252Z digest=sha256:cbba5664bd16ea64ef63380fb5050b4f3d4a7120ac3314de60d50d4ca6edbee8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.560287Z digest=sha256:f02d0d87a79b2853d76863f1eafba39429e5c674f882904ec7379b2fbd326da8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.564431Z digest=sha256:e3fb6b721215e64276d9ad383bf6f93170851882928355b6e8fea2c659df8222

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.568351Z digest=sha256:78f22834c167658830778cad6bfd4241bf7c2aa85c5c9d90f646b89ac04fb4ab

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.572312Z digest=sha256:36d8e9e8307e603f499bbf5a1d85d9eae94b907f6a813940ff29221759d5d37f

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:e3f2663120cc61bb81f515e89257328d453bf28096a6095c5a81256f7a837022

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.580991Z digest=sha256:05e08505e97afeaa43cc3b1883dc20119db3f4da05cd3c44d9c80bc1790c8ada

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.584994Z digest=sha256:22f30235ff0bc428c02c08d5119ff22fd159029b32aa234cb8da7ac6664c1b86

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=sha256:171ebba1cb8807df23ed51fbdb8a48fca00eb8e09d85ef94db4f21e0c30738cc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.592669Z digest=sha256:cbe71029eceaf91b168020216e7168291b9b1fb3e4a8ceebca002898a43ab670

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.596776Z digest=sha256:bd7eea3cc6bd801675d73b303b3eadf1a20b51dc0e556fc9a56519dd60869c53

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.600868Z digest=sha256:324be93aad99387d33e72a7d09a0adb200d5a028ecb91021f81d371c91dfa380

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.604998Z digest=sha256:826a771d039fe687744254a1399c454d883cc4190cb2c4d69229c11b715bfa3b

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
unresolved
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=sha256:93c2a774bafab72579109605dfb07a6b222c01ef6339812d07b07e305345c03d

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=sha256:0f61a2c2e9eb041b23bada6d431de9c2e44b7c230672b03e246b3742b8d303fe

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=sha256:1dfe1f83a7af6b91d55753c2afa0705a4e057755557eca52984e3edd4ca2db21

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.621714Z digest=sha256:76d27b3095bb29c4b8aa1c11e7f6a69fd7bbcea371034361c1b8247e85f5b23b

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:ef8284bbeeb6ea4ed05dbc6f8caa932e465adb7ce3ecaadde2a6483008d5a5a1

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.630301Z digest=sha256:e53463b06b836a6adc06c8621b009d5bd521578b3d0afd75b871fea07f529f82

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.634219Z digest=sha256:06547c22a62c836583b60b3c7af88b7de6b4b258e8a907a68ca183c58d9518d7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.639220Z digest=sha256:cc3164b47405cd14c685ed41ef7d07912a620c13b51fef5409f661f6366fc9aa

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.643802Z digest=sha256:7aa69bcf20b4d3118b3950aa9ff5277f2c76f1daa594d15c49e54f23331c4333

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:c7ae65849a7bebf797ce27ae4d705cb21ba393066ca243d8871785c72bb604e8

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.652321Z digest=sha256:65d015535554bd590ea973e63b7876b493d9e3101a15db114d09b46f06c9862b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.656543Z digest=sha256:44d493622e64b45ab7c6108d34831ad0152eb676480a63cc367d15a19f054091

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=sha256:4cb417d2ef70f75640ad94e6268c043b065038e22ab74326865eacaf05ebb140

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.664876Z digest=sha256:ccf35914cca74f8a68dfd7fa564dbed1a6daed72385b11a87ff9c9a2d1ecedfb

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=sha256:2defcf60d23af68691fa2b98048aa2e29379776ef0ddcc23fe9a2c36d7abedfc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.673583Z digest=sha256:b5b375ca51b6002cea8000ff187d424673d2e1515acc1f51ac3e27716db3e925

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.677632Z digest=sha256:12b453e2dc75c449123a1e1541e1e5db79a9810e5ba58010881e18f3d88b6518

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.682001Z digest=sha256:8983736a0da187e1ee0672d83858e221bc833cb2fce60a10bff13a88576de0cb

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:bf31743d0363557ce156dd3aedb2ae7b016448000412dacef27a6c823864343f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.690493Z digest=sha256:379a5e8f1c66cb17c0f493f5470dc3845caefe74c6d51458557d653af04b1911

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=sha256:0040ff8b5c697be6e934a4cd01a95f2e01b95ab05bd2bf3060a966f5694874da

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.698950Z digest=sha256:2ce4995cb0fca8de8d72410d2d8d2acb99873b2ee12dd72667449185aad29086

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:ac53ea1ccc6f55479fff1cabcb7eac3b8d1fe2d17c12cf520b46c91f72ff63b4

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.708322Z digest=sha256:f3f8b204ff5ac9947e0c5a2cff61d889c5f03d1f3b7376b86a83f9529254a49e

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T22:24:59.712422Z digest=sha256:e1b1335d14241498695a231c39b593091961b8161183cf8252cd1cd8e14ec07d

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:d7884eabce6b44b7f4d6cd585e3756c2c5bea018d8707f355a66457ab8e5c55b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T10:21:36.624663Z digest=sha256:89a870f8b4b3dab4b75e49c49607a9573d5da081962079f3ed4fdceebf3c8c5f

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=sha256:50bb9e6429768fc9e26dcd9d6f93d1375a47ac782417e661d3bd3c353b09d166

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T10:17:30.010781Z digest=sha256:c59a128a4b05350e322806aa8c2f17fedcc246dda314983e366d465a01f7ec8b

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=sha256:87c1dcdc71e2c9b2781d55be25a64e08bfeb789521db7ab4846962484f3ff01d