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Paper Citation Record · LEDGER

Advancing Question Generation with Joint Narrative and Difficulty Control

As of 18 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2506.06812.

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

pith.paper-citation-record.v1
2506.06812 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:53:18.380583Z

measured 13 of 13 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 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 fuzzy7
  • unresolved5
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fca2799e-fa5b-4cac-a383-08e953b60804 · outbound

This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

Advancing Question Generation with Joint Narrative and Difficulty Control DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T05:53:18.353435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:18.353435Z digest=sha256:f5e681170dcd4bc92806c51f2babe72f9919aedb867e06cc4e63686b8415b2c9

Observation 2630de3d-5fb6-483e-a4f2-f2e299fd6c0d · outbound

This paper cites In The Semantic Web – ISWC 2019: 18th International Semantic Web Conference, Auckland, New Zealand, October 26–30, 2019, Proceedings, Part I, page 382–398, Berlin, Hei- delberg.

Advancing Question Generation with Joint Narrative and Difficulty Control In The Semantic Web – ISWC 2019: 18th International Semantic Web Conference, Auckland, New Zealand, October 26–30, 2019, Proceedings, Part I, page 382–398, Berlin, Hei- delberg

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.505054Z

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.

source=pdf_text observed=2026-08-07T05:53:18.357225Z digest=sha256:a904977402959f831ac708e0971c5df1082e0ce72ecb9c34c47a035b4e2d77f3

Observation 6cdc66cd-2277-4ee8-9a4b-612009c377ad · outbound

This paper cites In Findings of the Asso- ciation for Computational Linguistics: ACL 2024 , pages 4715–4729, Bangkok, Thailand.

Advancing Question Generation with Joint Narrative and Difficulty Control In Findings of the Asso- ciation for Computational Linguistics: ACL 2024 , pages 4715–4729, Bangkok, Thailand

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.494372Z

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.

source=pdf_text observed=2026-08-07T05:53:18.360423Z digest=sha256:d45614e0d12bc4bfb9d64523d5ad25805dbcf9603262ca399a88b203fe7c35eb

Observation f5cb365c-a13d-4c62-98da-de53964a8610 · outbound

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

Advancing Question Generation with Joint Narrative and Difficulty Control RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T05:53:18.363636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:18.363636Z digest=sha256:d939475a2af42402ffad5f1ae65da162a370f8b91420ee3fbab75fdb31db81c8

Observation e6c4dd86-22ea-44f7-a55a-f76fa28e0442 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Advancing Question Generation with Joint Narrative and Difficulty Control DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T05:53:18.370709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:18.370709Z digest=sha256:228d7945efeee2dd7a420c2a69b2e98b72234d36b4137e402fa3758976c67f42

Observation 711add36-50f5-4f20-a730-3daa44c49e21 · outbound

This paper cites In Pro- ceedings of the 2022 Conference on Empirical Meth- ods in Natural Language Processing, pages 670–688, Abu Dhabi, United Arab Emirates.

Advancing Question Generation with Joint Narrative and Difficulty Control In Pro- ceedings of the 2022 Conference on Empirical Meth- ods in Natural Language Processing, pages 670–688, Abu Dhabi, United Arab Emirates

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.474367Z

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.

source=pdf_text observed=2026-08-07T05:53:18.374261Z digest=sha256:54ee276f2ad0963cc9c016cbc188ebbbe4073e2c86f22649d7abca9d69439700

Observation 594ff98e-43ea-4f51-939c-0be1d4962f1e · outbound

This paper cites why” and “how.

Advancing Question Generation with Joint Narrative and Difficulty Control why” and “how

Reference 13

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T05:53:18.452208Z

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.

source=pdf_text observed=2026-08-07T05:53:18.380583Z digest=sha256:407a1aea1e99e62c32e32d7ba163ea3fe81c1350d07ce9fc9998c6a82d8b44dc

Observation 4dad9f99-ca61-4cf6-a41b-4635ad164ef9 · outbound

This paper cites In Proceedings of the 2016 Conference on Empirical Methods in Natu- ral Language Processing, pages 2383–2392, Austin, Texas.

Advancing Question Generation with Joint Narrative and Difficulty Control In Proceedings of the 2016 Conference on Empirical Methods in Natu- ral Language Processing, pages 2383–2392, Austin, Texas

Reference 2016

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.484340Z

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.

source=pdf_text observed=2026-08-07T05:53:18.367609Z digest=sha256:d9a20b2847bcbabadba9942e99f04236b2886ba90a04712ac02153e119f5b454

Observation ebe7553a-7f2f-4ff9-b07c-ee9c5527ca38 · outbound

This paper cites an unresolved cited work.

Advancing Question Generation with Joint Narrative and Difficulty Control Unresolved cited work

Reference 2019

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:53:18.524847Z

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.

source=pdf_text observed=2026-08-07T05:53:18.346082Z digest=sha256:ca92d44164fc371861ef2bc21fc84db450ea58dba66b3ee1f00729ac8cba6b35

Observation 8f9a7391-44ec-433a-ab41-1cfd5b90d500 · outbound

This paper cites Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model.

Advancing Question Generation with Joint Narrative and Difficulty Control Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T05:53:18.337716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:53:18.337716Z digest=sha256:596191b5dd086810932bb5f24788caf1d341598aa621898f88a151b4a95251c4

Observation adc5fe4b-ff7b-4d7e-85d8-e39109f00bd4 · outbound

This paper cites In Find- ings of the Association for Computational Linguis- tics: ACL 2022, pages 2131–2146, Dublin, Ireland.

Advancing Question Generation with Joint Narrative and Difficulty Control In Find- ings of the Association for Computational Linguis- tics: ACL 2022, pages 2131–2146, Dublin, Ireland

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.515356Z

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.

source=pdf_text observed=2026-08-07T05:53:18.349575Z digest=sha256:543cde68a4cac7ff3c366dba904de93b1930d86c21713c34cbb53d35cc902b3f

Observation 77094945-8741-40db-834d-6b34eaf2c6f3 · outbound

This paper cites In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), pages 119–129, Toronto, Canada.

Advancing Question Generation with Joint Narrative and Difficulty Control In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), pages 119–129, Toronto, Canada

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.464070Z

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.

source=pdf_text observed=2026-08-07T05:53:18.377598Z digest=sha256:c6dcaebdf1550aa1beb64dbe2864f74734a354e00283cc11640e05c8cd76aadc

Observation 296ad0ad-e32c-47c9-832d-299e31f62cb0 · outbound

This paper cites In Proceed- ings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 17351–17370, Miami, Florida, USA.

Advancing Question Generation with Joint Narrative and Difficulty Control In Proceed- ings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 17351–17370, Miami, Florida, USA

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:53:18.534225Z

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.

source=pdf_text observed=2026-08-07T05:53:18.342356Z digest=sha256:efd792249f96e8527bed22bed9a00ab29e4251e7a5ffba0d20ca284895da4fa7

Pith citing papers

No inbound Pith citation observations are available.