Paper Citation Record · LEDGER

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence

As of 19 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2412.00883.

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

pith.paper-citation-record.v1
2412.00883 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:58:48.043232Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

14 of 14 outbound references displayed

verified exact0
verified fuzzy8
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 750c740c-20f1-45ac-989c-b6e267118a12 · outbound

This paper cites an unresolved cited work.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-12T04:58:48.395670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bff26d70-dfc1-4731-b685-17da6c507ff8 · outbound

This paper cites In NeurIPS.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence In NeurIPS

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.379263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cebd4b1b-af9e-4fc9-b3fa-b705459d8823 · outbound

This paper cites In NAACL, pages 3003–.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence In NAACL, pages 3003–

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.366695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a3e0df55-fa88-490f-a1d8-e64daa00cfd0 · outbound

This paper cites Fur- thermore, PS-NET incorporates curriculum ad- versarial training (CAT) (shown in Algorithm 1) to 2O progressively increase learning complexity.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence Fur- thermore, PS-NET incorporates curriculum ad- versarial training (CAT) (shown in Algorithm 1) to 2O progressively increase learning complexity

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.326197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c7cf7d25-d670-4b37-b254-8604f7856664 · outbound

This paper cites A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-12T04:58:47.983740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64c03b77-c33f-42b2-8f08-5a5cc731ded3 · outbound

This paper cites In NeuralPS, pages 3146–3154.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence In NeuralPS, pages 3146–3154

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.409397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 428041a5-be91-41b6-a118-16efa61577ed · outbound

This paper cites Improving neural networks by preventing co-adaptation of feature detectors.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence Improving neural networks by preventing co-adaptation of feature detectors

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-12T04:58:47.952673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee996dad-1fe9-4b8c-8fe2-b913b521e9c7 · outbound

This paper cites In NeurIPS, pages 5050–5060.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence In NeurIPS, pages 5050–5060

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.612470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aa11776c-7e6c-47c0-8ae8-eaa674edd804 · outbound

This paper cites SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-12T04:58:47.873008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5b11e3f-fd37-4652-ae0b-55bcd9e96911 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-12T04:58:47.974400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffb3b976-5c91-4765-bc07-333c0cbe162c · outbound

This paper cites In CVPR, pages 18392–18402.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence In CVPR, pages 18392–18402

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.469905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 08d72ab0-7d07-423b-8a16-4fd4182dc57a · outbound

This paper cites Yuanmeng Yan, Rumei Li, Sirui Wang, Fuzheng Zhang, Wei Wu, and Weiran Xu.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence Yuanmeng Yan, Rumei Li, Sirui Wang, Fuzheng Zhang, Wei Wu, and Weiran Xu

Reference 3013

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.353599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8cddf531-85e7-480d-9e63-1f7fd916cc9a · outbound

This paper cites Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu

Reference 4030

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T04:58:48.423185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fed66f58-e509-43e0-a045-68abe36f5481 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 5075

Resolution: unresolved; no resolver link, observed 2026-08-12T04:58:48.001845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.