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Paper Citation Record · LEDGER

Efficient Few-Shot Learning Without Prompts

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2209.11055.

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

pith.paper-citation-record.v1
2209.11055 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 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 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:48:04.612158Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

101
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9d7f335a-77db-4c0c-976d-7e24fec9d34a · inbound

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference cites this paper.

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference Efficient Few-Shot Learning Without Prompts

Reference 190

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verified exact
arxiv_id, observed 2026-05-20T17:46:46.965362Z

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=arxiv_source observed=2026-05-20T17:46:46.845424Z digest=sha256:c7d1053e7739823ec98a101fe0456fd49abd67602904691408c20c8982500dc7

Observation 81a4cfb5-6edb-41b7-a1ee-8c9f2f1cc0fb · inbound

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation cites this paper.

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation Efficient Few-Shot Learning Without Prompts

Reference 40

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no resolver link, observed 2026-08-07T14:48:04.612158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:48:04.612158Z digest=sha256:510b2c170485aa1a9d9d66f6f7f850173585c3e7ccd5a7f88d1ef2c733ff49cb

Observation fbfcf097-954d-4d6b-a474-5cdb1c35ae79 · inbound

Unveiling Dual Quality in Product Reviews: An NLP-Based Approach cites this paper.

Unveiling Dual Quality in Product Reviews: An NLP-Based Approach Efficient Few-Shot Learning Without Prompts

Reference 40

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no resolver link, observed 2026-08-07T14:22:24.068661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:22:24.068661Z digest=sha256:6e2f728159e02472232455dd79044c465b7717eaec3368d9a67f4fc16c9ef56b

Observation aadfd0b1-2428-4dfa-a44b-926680327b6e · inbound

Evaluating the Performance and Efficiency of Sentence-BERT for Code Comment Classification cites this paper.

Evaluating the Performance and Efficiency of Sentence-BERT for Code Comment Classification Efficient Few-Shot Learning Without Prompts

Reference 7

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unresolved
no resolver link, observed 2026-08-07T05:12:42.922777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:12:42.922777Z digest=sha256:8f5cf3f25cf64280c54c058f1e6a52083258f790d66779332056d75f2600892d

Observation f80c6234-75a5-4f17-8ed7-f292b106d702 · inbound

On The Impact of Merge Request Deviations on Code Review Practices cites this paper.

On The Impact of Merge Request Deviations on Code Review Practices Efficient Few-Shot Learning Without Prompts

Reference 44

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no resolver link, observed 2026-08-07T05:04:19.618270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:04:19.618270Z digest=sha256:1b9ff2320036984b5b7402aaba412f302ac1793a4108d9d57a094f4f876a552d

Observation 978ef08b-7efb-47d5-b30d-8d0ac701d596 · inbound

Self-Anchored Attention Model for Sample-Efficient Classification of Prosocial Text Chat cites this paper.

Self-Anchored Attention Model for Sample-Efficient Classification of Prosocial Text Chat Efficient Few-Shot Learning Without Prompts

Reference 70

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unresolved
no resolver link, observed 2026-08-07T04:56:55.411606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:56:55.411606Z digest=sha256:e75462b3f1328f143acbdbc99d49a6417c66f05516aaf5c766d5975ff91b8eaa

Observation e3648440-0420-432f-8a9f-24dc695e9a86 · inbound

The Narrative Construction of Generative AI Efficacy by the Media: A Case Study of the Role of ChatGPT in Higher Education cites this paper.

The Narrative Construction of Generative AI Efficacy by the Media: A Case Study of the Role of ChatGPT in Higher Education Efficient Few-Shot Learning Without Prompts

Reference 2020

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no resolver link, observed 2026-08-06T18:03:54.940500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:03:54.940500Z digest=sha256:c41a9a58516f6ad90c655c71a347556b405066339a6b1523e17d142d2ad07639

Observation 9e533ad9-00ec-4dea-9be1-2de6295b1220 · inbound

ConspirED: A Dataset for Cognitive Traits of Conspiracy Theories and Large Language Model Safety cites this paper.

ConspirED: A Dataset for Cognitive Traits of Conspiracy Theories and Large Language Model Safety Efficient Few-Shot Learning Without Prompts

Reference 62

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unresolved
no resolver link, observed 2026-08-05T15:09:05.963638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:09:05.963638Z digest=sha256:a43ddadeaa5f3e8553c638a49d272c8b758e36e2c777bab0e7e79e4e1b53a7aa

Observation a0c62731-83bc-4780-8e52-00421f36e5f0 · inbound

Few-Shot Query Intent Detection via Relation-Aware Prompt Learning cites this paper.

Few-Shot Query Intent Detection via Relation-Aware Prompt Learning Efficient Few-Shot Learning Without Prompts

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T05:21:30.867771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:21:30.867771Z digest=sha256:ebc9fcfceb06492a635d39aaba79c4332f8e187ebae5109ec35855231303ca1b

Observation 2155b975-3303-40d7-b96b-003197b3556c · inbound

Predicting Intermittent Job Failure Categories for Diagnosis Using Few-Shot Fine-Tuned Language Models cites this paper.

Predicting Intermittent Job Failure Categories for Diagnosis Using Few-Shot Fine-Tuned Language Models Efficient Few-Shot Learning Without Prompts

Reference 39

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verified exact
arxiv_id, observed 2026-05-16T09:17:40.200103Z

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=2026-05-16T09:17:09.823817Z digest=sha256:50dfd567a065b4123a4b92dd17c5b4c08b31857532cb0774f55f0ec59cd8c1f5

Observation e675bdb8-a079-4f4c-b88a-1557aacd1fdd · inbound

LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification cites this paper.

LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification Efficient Few-Shot Learning Without Prompts

Reference 13

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verified exact
arxiv_id, observed 2026-05-15T17:06:19.249032Z

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=2026-05-15T17:03:04.705363Z digest=sha256:a10bc5a87659b0f7e49429272b207f612c3775ea12ea530991284aaae848b231

Observation 84a90ada-7032-413d-a2fc-41a1e3f0de69 · inbound

Characterizing Resource Sharing Practices on Underground Internet Forum Synthetic Non-Consensual Intimate Image Content Creation Communities cites this paper.

Characterizing Resource Sharing Practices on Underground Internet Forum Synthetic Non-Consensual Intimate Image Content Creation Communities Efficient Few-Shot Learning Without Prompts

Reference 49

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verified exact
arxiv_id, observed 2026-05-11T09:01:00.921663Z

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=2026-05-10T16:18:03.390618Z digest=sha256:18392d3b00949a636e9f9807475b1ebc1bb465635c4f88ee393e10c22db24356

Observation 76f86620-4f54-4088-8ef5-96d83e02e508 · inbound

Cross-Domain Query Translation for Network Troubleshooting: A Multi-Agent LLM Framework with Privacy Preservation and Self-Reflection cites this paper.

Cross-Domain Query Translation for Network Troubleshooting: A Multi-Agent LLM Framework with Privacy Preservation and Self-Reflection Efficient Few-Shot Learning Without Prompts

Reference 21

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metadata mismatch
arxiv_id, observed 2026-05-10T13:45:27.721801Z

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=2026-05-10T13:44:05.443209Z digest=sha256:ce3c295c4d6a7b0b5d53665cd7c12ceb525475886c4d6e982f31230f2706c198

Observation 81a12d27-4f00-4baa-b85c-9923a1db45a4 · inbound

Cross-Domain Query Translation for Network Troubleshooting: A Multi-Agent LLM Framework with Privacy Preservation and Self-Reflection cites this paper.

Cross-Domain Query Translation for Network Troubleshooting: A Multi-Agent LLM Framework with Privacy Preservation and Self-Reflection Efficient Few-Shot Learning Without Prompts

Reference 21

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metadata mismatch
arxiv_id, observed 2026-05-21T01:09:20.491892Z

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=2026-05-21T01:06:00.831147Z digest=sha256:19864037f026c0028df92f8b375ad769f21fbeb8bd55aa713418b778103b200d

Observation 9ba4c14c-2651-4baf-a3f1-d63cf7439336 · inbound

Domain-Specific Query Understanding for Automotive Applications: A Modular and Scalable Approach cites this paper.

Domain-Specific Query Understanding for Automotive Applications: A Modular and Scalable Approach Efficient Few-Shot Learning Without Prompts

Reference 4

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metadata mismatch
arxiv_id, observed 2026-05-16T13:37:56.645797Z

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=2026-05-16T13:37:13.043968Z digest=sha256:7fa13601b42df8544a2eaae0f5b5ba8026a71159c9230350d32a946e08510734

Observation 79a84a26-aa25-43aa-b932-7e339ed4d55e · inbound

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models cites this paper.

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models Efficient Few-Shot Learning Without Prompts

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:40:40.398227Z

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=2026-05-08T18:14:03.049005Z digest=sha256:2fd046796c1b6d8e2d25b2958f6c8fd69545cfc98e2c56f3163773febf4e2af1

Observation 38da6f7d-ece7-4d56-be14-76b47c31ac6c · inbound

Retrieving Floods without Floodlights: Topic Models as Binary Classifiers for Extreme Climate Events in German News cites this paper.

Retrieving Floods without Floodlights: Topic Models as Binary Classifiers for Extreme Climate Events in German News Efficient Few-Shot Learning Without Prompts

Reference 24

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metadata mismatch
arxiv_id, observed 2026-05-12T10:56:30.287165Z

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=2026-05-07T16:56:18.930883Z digest=sha256:30d76ea9c0c6c6084f3a9e1ea11723536578c413e13cdbc1b810930e047dfb5c

Observation 8ee93365-5e02-4353-988c-b7114f1c1674 · inbound

Quantum Parity Representations: Learnable Basis Discovery, Encoders, and Shadow Deployment cites this paper.

Quantum Parity Representations: Learnable Basis Discovery, Encoders, and Shadow Deployment Efficient Few-Shot Learning Without Prompts

Reference 6

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arxiv_id, observed 2026-05-13T02:32:06.633566Z

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=2026-05-13T02:28:34.197942Z digest=sha256:3c143af65e902c50fea6fdd56ad6df93321516a077f095fe3b16080df5cf3e30

Observation 42170a91-2101-46e7-9f0b-0d9100c39aea · inbound

Much of Geospatial Web Search Is Beyond Traditional GIS cites this paper.

Much of Geospatial Web Search Is Beyond Traditional GIS Efficient Few-Shot Learning Without Prompts

Reference 26

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metadata mismatch
arxiv_id, observed 2026-05-13T01:22:00.841815Z

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=2026-05-13T01:19:26.399524Z digest=sha256:ced7e7bfe0f586ec16dfe6af86538cd9d6829532fcca2d6dc3d9f4b6dbf4dbea

Observation e33e246f-554d-42fb-9ea6-db346c716bfb · inbound

Much of Geospatial Web Search Is Beyond Traditional GIS cites this paper.

Much of Geospatial Web Search Is Beyond Traditional GIS Efficient Few-Shot Learning Without Prompts

Reference 27

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arxiv_id, observed 2026-06-30T22:05:05.184196Z

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=2026-06-30T21:58:45.277252Z digest=sha256:21ae2a44cd1edd49cac1c3b085afef3f6053c09abe3e7c0ab661d6b1fd5a63c1

Observation 0212eb99-06df-4bce-a854-ced2d675c533 · inbound

CR4T: Rewrite-Based Guardrails for Adolescent LLM Safety cites this paper.

CR4T: Rewrite-Based Guardrails for Adolescent LLM Safety Efficient Few-Shot Learning Without Prompts

Reference 57

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verified exact
arxiv_id, observed 2026-05-22T09:24:45.883483Z

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=arxiv_source observed=2026-05-22T09:21:59.200523Z digest=sha256:33d41392d841fc8ff93e0423e1c367029b6d52935ac0e2618a902150262c4af9

Observation 8713978c-3c7f-4b9a-bdd1-09b471688843 · inbound

Opir: Efficient Multi-Task Safety Classification for Toxicity, Jailbreaks, Hate Speech, and Harmful Content cites this paper.

Opir: Efficient Multi-Task Safety Classification for Toxicity, Jailbreaks, Hate Speech, and Harmful Content Efficient Few-Shot Learning Without Prompts

Reference 35

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verified exact
arxiv_id, observed 2026-06-29T09:13:15.919148Z

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=2026-06-29T09:11:58.843585Z digest=sha256:2a1521b2fa83888b000c99b56eab91e87ac0e6e54758bb5e1b70599e4cc622d5

Observation 6354a5c9-0603-4df2-83b1-22fb3be1974e · inbound

Multilingual Fact-Checking at Scale: Fine-Tuned Compact Models vs LLMs cites this paper.

Multilingual Fact-Checking at Scale: Fine-Tuned Compact Models vs LLMs Efficient Few-Shot Learning Without Prompts

Reference 11

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metadata mismatch
arxiv_id, observed 2026-07-02T22:27:25.370613Z

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=2026-06-27T18:58:55.712400Z digest=sha256:2685905f9b508a31ffc8e81e2855ec95ebe585e8374f77fb6c59c02d4e1eba34

Observation 04704132-0917-4749-ae27-fbc841fd1253 · inbound

Detecting Knowledge Gaps from Conversational AI Interactions Using Curriculum Prerequisite Graphs cites this paper.

Detecting Knowledge Gaps from Conversational AI Interactions Using Curriculum Prerequisite Graphs Efficient Few-Shot Learning Without Prompts

Reference 16

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verified exact
arxiv_id, observed 2026-07-03T05:47:42.054676Z

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=2026-06-27T13:01:51.010436Z digest=sha256:250037a630106cf82d644fe25a8d1d657f623302ffcb25e776521707bbd4a6e8

Observation 36cc5858-1f10-4c9f-a812-9e2112770516 · inbound

From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline cites this paper.

From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline Efficient Few-Shot Learning Without Prompts

Reference 28

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unresolved
no resolver link, observed 2026-07-11T19:05:55.879132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T19:05:55.879132Z digest=sha256:d5bb78fd6f6ae08e33f4bbc69440b7d0a03db72a1d6dff47be075897414b8145

Observation de0d6ba7-5a77-4e59-8924-688866455480 · inbound

A Longitudinal Analysis of Public Discourse on AI Ethics in Education Using Twitter Data cites this paper.

A Longitudinal Analysis of Public Discourse on AI Ethics in Education Using Twitter Data Efficient Few-Shot Learning Without Prompts

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-15T07:14:38.560633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T07:14:38.560633Z digest=sha256:acf0ca0605aa20caa5d568facaa32a60b9a89cf7c9559990f6fc44773069fa19

Observation 16630b83-2afd-47c6-acb1-a8ccd58b24cd · inbound

Test-Time Scaling via Error Localization cites this paper.

Test-Time Scaling via Error Localization Efficient Few-Shot Learning Without Prompts

Reference 158

Resolution
unresolved
no resolver link, observed 2026-08-01T07:28:34.426364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:28:34.426364Z digest=sha256:3106b700a4dc777b15df421d73fe95c422a4b78ea89dd0a3c8bdb4a820540345

Observation b31ef1b5-be68-4428-9359-8161787a2b71 · inbound

How Much Does a Reasoning Summary Reveal? An Observability Ladder for Large Language Models cites this paper.

How Much Does a Reasoning Summary Reveal? An Observability Ladder for Large Language Models Efficient Few-Shot Learning Without Prompts

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-04T15:22:55.720055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T15:22:55.720055Z digest=sha256:cf7dcbbdef58c52f32b24ecf2ac8a3a1a6f9863a0863a907524275031f9ae418