Paper Citation Record · LEDGER

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa

As of 19 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2505.00013.

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

pith.paper-citation-record.v1
2505.00013 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:22:58.217380Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T09:45:05.825373Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:58:03.236411Z

Reference resolution

29 of 29 outbound references displayed

verified exact3
verified fuzzy18
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b48dd59b-357d-4ac3-a5cf-54f0bdd1f533 · outbound

This paper cites : Opinion mining and sentiment analysis.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa : Opinion mining and sentiment analysis

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.685113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 096e0744-ae0a-4cba-ae16-ec147fff7d51 · outbound

This paper cites Springer, ??? (2022).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Springer, ??? (2022)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.674760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c8de2453-91cf-4926-bebf-fa2188f29046 · outbound

This paper cites arXiv p reprint arXiv:2311.11250 (2023).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa arXiv p reprint arXiv:2311.11250 (2023)

Reference 3

Resolution: verified exact; raw_fallback, observed 2026-08-16T11:22:58.470700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 62cc9094-0ad6-43d1-83f6-970e7c1e71c9 · outbound

This paper cites Journal of computational science 2(1), 1–8 (2011).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Journal of computational science 2(1), 1–8 (2011)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.664871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad0313cc-b2d2-4868-a70c-4054b149955f · outbound

This paper cites In: Proceedings of the Workshop on Computational Ling uistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: Proceedings of the Workshop on Computational Ling uistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, pp

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.654082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fada6b29-3f07-4d90-aac7-790a6f84f45b · outbound

This paper cites Proceedings of the ACM on Huma n- Computer Interaction 1(CSCW), 1–27 (2017) 1https://pypi.org/project/deberta-emotion-predictor 11.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Proceedings of the ACM on Huma n- Computer Interaction 1(CSCW), 1–27 (2017) 1https://pypi.org/project/deberta-emotion-predictor 11

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.643636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a0570fc1-46fb-4e1d-aa7c-2cbc7bf28c94 · outbound

This paper cites In: Proceedings of the 38th In ternational ACM SIGIR Conference on Research and Development in Information Re trieval, pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: Proceedings of the 38th In ternational ACM SIGIR Conference on Research and Development in Information Re trieval, pp

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.631888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1dbe4c1f-b4c0-469b-adfb-38333bb68aeb · outbound

This paper cites In: Proceedings of the 25th International Conference on World Wide Web, pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: Proceedings of the 25th International Conference on World Wide Web, pp

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.621076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28322b47-71b7-46eb-87a2-714a3e4e5b4d · outbound

This paper cites I n: Theories of Emotion, pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa I n: Theories of Emotion, pp

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.610552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a7f82c43-99e4-4eca-9e5d-56bdd43ea42a · outbound

This paper cites arXiv preprint arXiv:2 011.01612 (2020).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa arXiv preprint arXiv:2 011.01612 (2020)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.599745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a8961156-a0b0-4cbd-ad07-8d4823c9790f · outbound

This paper cites DENS: A Dataset for Multi-class Emotion Analysis.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa DENS: A Dataset for Multi-class Emotion Analysis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T11:22:58.149823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b84ba7d1-f6b5-4cc6-9c72-88d6c578a415 · outbound

This paper cites In: Proc.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: Proc

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.588966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1495bfeb-c5cb-4a6a-a741-c2d3104ea069 · outbound

This paper cites IEEE Access 12, 19752–19764 (2024).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa IEEE Access 12, 19752–19764 (2024)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.578027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9da4c68c-12bd-4ba3-9dfd-bde6d5aee33a · outbound

This paper cites Speech Communica tion 156, 103004 (2024).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Speech Communica tion 156, 103004 (2024)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.566543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e2c1694c-4fb9-482c-9cb7-ef8eb906027a · outbound

This paper cites Scientiﬁc Reports 13(1), 21785 (2023).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Scientiﬁc Reports 13(1), 21785 (2023)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.555089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ccc07f45-0cc0-434b-9ebf-4aee0b10a6f0 · outbound

This paper cites Applied Mathematics and Nonlinear Sciences 10 (2025) https://doi.org/10.2478/amns-2025-0606.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Applied Mathematics and Nonlinear Sciences 10 (2025) https://doi.org/10.2478/amns-2025-0606

Reference 16

Resolution: verified exact; doi, observed 2026-08-16T11:22:58.250238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28d92c0b-53fb-45d9-b772-0a2a9517a881 · outbound

This paper cites Topic Modeling and Sentiment Analysis on Japanese Online Media's Coverage of Nuclear Energy.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Topic Modeling and Sentiment Analysis on Japanese Online Media's Coverage of Nuclear Energy

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T11:22:58.172584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7546f456-4ac3-45bd-89f0-9a843bfb0d8b · outbound

This paper cites In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human L anguage 12 Technologies, pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human L anguage 12 Technologies, pp

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.544281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d555453-e87f-4277-abd2-2734f03136de · outbound

This paper cites an unresolved cited work.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:22:58.530711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 23282bac-43c9-4c0c-9f95-20ed8152cd41 · outbound

This paper cites In: P roceedings of the 30th Annual Meeting of the Association for Natural Langua ge Process- ing (NLP2024), Nagoya, Japan, pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: P roceedings of the 30th Annual Meeting of the Association for Natural Langua ge Process- ing (NLP2024), Nagoya, Japan, pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.517959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ef5edfaf-820a-4e22-9688-be20bd9d776d · outbound

This paper cites In: Foru m on Data Engineering and Information Management (DEIM2024), Paper T1- B-8-03, Japan (2024).

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: Foru m on Data Engineering and Information Management (DEIM2024), Paper T1- B-8-03, Japan (2024)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.505989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 02db4266-d344-43de-b427-29fef8aff75f · outbound

This paper cites In: 2020 17 th International Computer Conference on Wavelet Active Media Technology and Info rmation Processing (ICCW AMTIP), pp.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa In: 2020 17 th International Computer Conference on Wavelet Active Media Technology and Info rmation Processing (ICCW AMTIP), pp

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.494316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation efeb4a33-c9c2-4a15-ab44-13220a8d4e0c · outbound

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

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T11:22:58.194335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41b92c5f-1259-4e98-8afc-0995a73d4a2b · outbound

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

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T11:22:58.198105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52e703dd-b199-4277-b9c6-9862a5fc76c9 · outbound

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

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa GoEmotions: A Dataset of Fine-Grained Emotions

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T11:22:58.202234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03bab130-a22a-402d-a40a-5211f95cd7b6 · outbound

This paper cites Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-08-16T11:22:58.348567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e290a38-47f7-4835-b6f4-76b785183d0b · outbound

This paper cites https://arxiv.org/abs/2503.18253.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa https://arxiv.org/abs/2503.18253

Reference 27

Resolution: verified exact; raw_fallback, observed 2026-08-16T11:22:58.330006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7090dc11-067c-43cd-963b-54556bc8932d · outbound

This paper cites TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T11:22:58.213229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8aa8e249-6fbf-4037-9ba4-1def9642e0a5 · outbound

This paper cites https://openai.com/index/gpt-4o.

Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa https://openai.com/index/gpt-4o

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:22:58.483007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 614a0367-31ab-416f-8a23-63a04b5da452 · inbound

I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System cites this paper.

I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:58:03.237700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.