Paper Citation Record · LEDGER

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2505.16225.

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

pith.paper-citation-record.v1
2505.16225 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:46.763100Z

measured 36 of 36 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

36 of 36 outbound references displayed

verified exact2
verified fuzzy8
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44c774ba-1e4c-43bc-8344-a7129b7ef201 · outbound

This paper cites M., Bohnet, B., Rosias, L., Chan, S.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning M., Bohnet, B., Rosias, L., Chan, S

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:49.952799Z

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.

Observation 27a70b40-34e8-4690-9982-4c7a6ca5290b · outbound

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

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning In-Context Learning with Long-Context Models: An In-Depth Exploration

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.428377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d11548b-b947-41d7-b8a2-79444d4955e1 · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.510056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c4c4b9c-e657-46c7-ad2c-4258f744ba19 · outbound

This paper cites FastGAS: Fast Graph-based Annotation Selection for In-Context Learning.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning FastGAS: Fast Graph-based Annotation Selection for In-Context Learning

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:09:47.893781Z

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.

Observation 277abd81-4632-4e7f-956a-54db7f93624a · outbound

This paper cites Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.013943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d596180-3436-4d38-9648-9711953afb01 · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.146271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a7bc83b-72d7-4f21-8392-a6b8aa9e2418 · outbound

This paper cites Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.637290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 542d2853-0d9a-4f8b-8b5d-fb4d94966913 · outbound

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

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning In-Context Learning with Many Demonstration Examples

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.712823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ad850e-624c-4ae7-9c86-67b414a48740 · outbound

This paper cites Long-context LLMs Struggle with Long In-context Learning.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Long-context LLMs Struggle with Long In-context Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.774129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43014f30-f482-4cdf-849d-8da5cd9e8479 · outbound

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

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning What Makes Good In-Context Examples for GPT-$3$?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.888545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94fa8163-c4d3-4191-bb24-5167f9610be8 · outbound

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

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:44.074542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33ccc29b-9a80-40c4-bc51-ac0598212838 · outbound

This paper cites In-Context Learning with Iterative Demonstration Selection.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning In-Context Learning with Iterative Demonstration Selection

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:44.406330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62a4e4ff-807a-4f30-9420-2d8c2665c841 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:44.570500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9773e69-249f-460b-adba-1800c1180bd1 · outbound

This paper cites Learning to retrieve prompts for in-context learning.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Learning to retrieve prompts for in-context learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:49.450913Z

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.

Observation 3bc57197-ae01-4c83-a78e-3241e8619101 · outbound

This paper cites Selective Annotation Makes Language Models Better Few-Shot Learners.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Selective Annotation Makes Language Models Better Few-Shot Learners

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:45.125390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07eaf020-7728-4bad-923a-f5a67efe8ead · outbound

This paper cites W., Chowdhery, A., Le, Q., Chi, E., Zhou, D., et al.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning W., Chowdhery, A., Le, Q., Chi, E., Zhou, D., et al

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:49.273286Z

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.

Observation 1300cc60-68b8-44fd-bbc0-440e0be44969 · outbound

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

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:45.429468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8783880f-34cd-4d53-8ac8-de10203aee2b · outbound

This paper cites Learning to Retrieve In-Context Examples for Large Language Models.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Learning to Retrieve In-Context Examples for Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:45.697415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33f96c4b-a84f-49ca-980b-b38f54ff3144 · outbound

This paper cites Are Large Language Models Good In-context Learners for Financial Sentiment Analysis?.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Are Large Language Models Good In-context Learners for Financial Sentiment Analysis?

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:09:47.080129Z

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.

Observation 4d8ec9e0-19d2-412d-9d3e-c99b73549966 · outbound

This paper cites More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:45.969946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 241164e3-05e1-4e0c-9d04-f8e3587a8cb1 · outbound

This paper cites A Survey of Large Language Models.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning A Survey of Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:46.107837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ac60ef3-b72e-4509-ae8c-8d65cf337254 · outbound

This paper cites an unresolved cited work.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:09:49.114369Z

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.

Observation ffb24d5c-207c-4b44-a095-20856e767d0a · outbound

This paper cites an unresolved cited work.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:09:48.959036Z

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.

Observation c96b6848-02e3-412e-b1de-9eab88c2f71f · outbound

This paper cites (2018), we set σ as the identity function and W as the identity matrix.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning (2018), we set σ as the identity function and W as the identity matrix

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:48.721004Z

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.

Observation 8b9da085-9041-450c-b574-a4a606854217 · outbound

This paper cites What is the article about?.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning What is the article about?

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:48.450415Z

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.

Observation 1116cda8-6e83-46db-9d22-5bc39c367f0c · outbound

This paper cites Sentence: Pharmaceuticals group Orion Corp reported a fall in its third-quarter earnings, which were impacted by larger expenditures on R&D and marketing. Label: negative.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Sentence: Pharmaceuticals group Orion Corp reported a fall in its third-quarter earnings, which were impacted by larger expenditures on R&D and marketing. Label: negative

Reference 1937

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:48.227189Z

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.

Observation 137e7d6a-f8de-4614-8f9e-44223a53200e · outbound

This paper cites B., and Lapata, M.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning B., and Lapata, M

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:49.618993Z

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.

Observation d09607da-e044-4ab4-9269-beea4dbcb0ec · outbound

This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.940547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b228e8d-c087-4e51-a1b4-8c3fba67edf7 · outbound

This paper cites Unifying Graph Convolutional Neural Networks and Label Propagation.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Unifying Graph Convolutional Neural Networks and Label Propagation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:45.569126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f367d205-dd93-41b7-be88-df6edaf08031 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:44.851478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23a1121b-0a62-4560-9ac8-898239de4ca6 · outbound

This paper cites Efficient Intent Detection with Dual Sentence Encoders.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Efficient Intent Detection with Dual Sentence Encoders

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.604095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c81ba85c-edb7-42e1-b1b1-06c4df76d0d8 · outbound

This paper cites Multi-Dimensional Evaluation of Text Summarization with In-Context Learning.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Multi-Dimensional Evaluation of Text Summarization with In-Context Learning

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:43.340125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a8413dd-c119-4635-ae4d-7266a9048d9b · outbound

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

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Revisiting In-Context Learning with Long Context Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.345000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed058904-0623-4365-b542-bd74f55a7c02 · outbound

This paper cites A., Wang, J.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning A., Wang, J

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:09:49.820095Z

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.

Observation cf5339df-b526-43a3-8924-5dd81d0268a2 · outbound

This paper cites In-context Examples Selection for Machine Translation.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning In-context Examples Selection for Machine Translation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.234982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba0e3324-869b-4cca-8bd2-939fa5b0cf13 · outbound

This paper cites GoEmotions: A Dataset of Fine-Grained Emotions.

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning GoEmotions: A Dataset of Fine-Grained Emotions

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:42.852146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.