Paper Citation Record · LEDGER

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification

As of 9 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2502.05923.

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

pith.paper-citation-record.v1
2502.05923 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:27:59.728697Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

13 of 13 outbound references displayed

verified exact0
verified fuzzy6
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0000495e-885a-4e42-8622-b4f992e50a5b · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T17:27:59.685914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 579856b0-4433-4615-b192-cfc3459b7ef4 · outbound

This paper cites In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 10513– 10529, Bangkok, Thailand.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 10513– 10529, Bangkok, Thailand

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:27:59.840027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bcc2ec1b-23cb-4a09-9e52-22a676ecd33e · outbound

This paper cites Kavel Rao, Liwei Jiang, Valentina Pyatkin, Yuling Gu, Niket Tandon, Nouha Dziri, Faeze Brahman, and Yejin Choi.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification Kavel Rao, Liwei Jiang, Valentina Pyatkin, Yuling Gu, Niket Tandon, Nouha Dziri, Faeze Brahman, and Yejin Choi

Reference 631

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:27:59.849803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 01a2f8e3-12b6-4798-9e04-0a2ddf49ac5a · outbound

This paper cites MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

Reference 1955

Resolution: unresolved; no resolver link, observed 2026-08-08T17:27:59.642737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be9de912-f5da-4877-bde1-69fb5363c533 · outbound

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

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification In-Context Learning with Long-Context Models: An In-Depth Exploration

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-08T17:27:59.634751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539a68eb-f573-409a-9b3a-7349f17c9672 · outbound

This paper cites In Proceedings of 52nd Annual Meet- ing of the Association for Computational Linguis- tics: System Demonstrations , pages 55–60, Balti- more, Maryland.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification In Proceedings of 52nd Annual Meet- ing of the Association for Computational Linguis- tics: System Demonstrations , pages 55–60, Balti- more, Maryland

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:27:59.870326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e54ee77c-5958-4dae-9ad3-92e56eec23c8 · outbound

This paper cites Snorkel: Rapid Training Data Creation with Weak Supervision.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification Snorkel: Rapid Training Data Creation with Weak Supervision

Reference 2017

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T17:27:59.780160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 724b341e-b8e7-4a37-98f4-e29922dc5692 · outbound

This paper cites In ARISE , we use bootstrapping approach for data filtering and apply our filtering on synthetically generated data, instead of unlabeled data from an existing corpus.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification In ARISE , we use bootstrapping approach for data filtering and apply our filtering on synthetically generated data, instead of unlabeled data from an existing corpus

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:27:59.829739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 082f053a-8c8e-4d8c-bd54-aef7352de9a5 · outbound

This paper cites GPT-4 Technical Report.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification GPT-4 Technical Report

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-08T17:27:59.655103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebd686ee-883e-4ef9-b122-fc97797ab4af · outbound

This paper cites In Findings of the Association for Com- putational Linguistics: ACL-IJCNLP 2021 , pages 4640–4651.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification In Findings of the Association for Com- putational Linguistics: ACL-IJCNLP 2021 , pages 4640–4651

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:27:59.880324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 78f97eb9-885f-48c9-b2b3-ef06169cc581 · outbound

This paper cites Deep Biaffine Attention for Neural Dependency Parsing.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification Deep Biaffine Attention for Neural Dependency Parsing

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T17:27:59.639158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36827dbe-3559-405c-aadd-9efa3cb8e055 · outbound

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

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification Long-context LLMs Struggle with Long In-context Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-08T17:27:59.646167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c589a93d-cac4-4d86-a9e9-7b2d7772c311 · outbound

This paper cites arXiv e-prints, pages arXiv– 2401.

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification arXiv e-prints, pages arXiv– 2401

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:27:59.860263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.