Paper Citation Record · LEDGER

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking

As of 8 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.09935.

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

pith.paper-citation-record.v1
2507.09935 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:48:38.312580Z

measured 23 of 23 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 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

23 of 23 outbound references displayed

verified exact3
verified fuzzy2
unresolved16
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6122085f-2a60-413a-a24a-4dede0928f27 · outbound

This paper cites A., Löser, A.: SECTOR: A Neural Model for Coherent Topic Segmentation and Classification.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking A., Löser, A.: SECTOR: A Neural Model for Coherent Topic Segmentation and Classification

Reference 1

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T17:48:40.345325Z

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.

Observation 77d44f6b-6aee-4e23-bb4a-54cd5f7fbeea · outbound

This paper cites In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL).

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL)

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T17:48:38.984733Z

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.

Observation c91550df-9152-4765-935a-a28a4af02690 · outbound

This paper cites In: Machine Learning 34, 177–210 (1999).

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking In: Machine Learning 34, 177–210 (1999)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:36.813091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e57a531-2c78-4a1c-b2f9-cf18fbffd965 · outbound

This paper cites Reading Wikipedia to Answer Open-Domain Questions.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking Reading Wikipedia to Answer Open-Domain Questions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:36.891373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 236f16aa-01cd-4632-8cd1-5dd5757be35f · outbound

This paper cites A., Gardner, M.: A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking A., Gardner, M.: A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:36.973030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b0176df-6814-4709-9589-4ee3151a3d4a · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.042357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69e1c6ee-99a3-43e2-a547-fa8ec0dcc3fd · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.108474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9eb6a0e-6827-42d4-b998-2dc1ca111800 · outbound

This paper cites A.: Multi-paragraph segmentation of expository text.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking A.: Multi-paragraph segmentation of expository text

Reference 8

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:48:39.539741Z

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.

Observation 146e6f57-720d-4640-8d3e-73852258e299 · outbound

This paper cites In: IEEE Transactions on Neural Networks and Learning Systems (2021).

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking In: IEEE Transactions on Neural Networks and Learning Systems (2021)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.277822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9861367-8ec5-407b-a250-3df72ecb113d · outbound

This paper cites LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.354322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3266622-8327-409b-8201-7a176f414d4f · outbound

This paper cites doi.org/10.48550/arXiv.2409.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking doi.org/10.48550/arXiv.2409

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.448863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6492ba90-2f67-4ba6-90b7-9243088cc987 · outbound

This paper cites https://github.com/FullStackRetrieval- com/RetrievalTutorials/blob/main/tutorials/LevelsOfTextSplitting/5_Levels_ Of_Text_Splitting.ipynb.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking https://github.com/FullStackRetrieval- com/RetrievalTutorials/blob/main/tutorials/LevelsOfTextSplitting/5_Levels_ Of_Text_Splitting.ipynb

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:40.145737Z

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.

Observation 81bb41d2-e1e9-4b98-b57d-0b24f6ce208c · outbound

This paper cites M., Melis, G., Grefenstette, E.: The NarrativeQA Reading Comprehension Challenge.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking M., Melis, G., Grefenstette, E.: The NarrativeQA Reading Comprehension Challenge

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.578283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54a2d7a7-b32d-45e8-8e03-5f651c670fc7 · outbound

This paper cites In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Lan- guage Technologies, Volume 2 (Short Papers), pp.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Lan- guage Technologies, Volume 2 (Short Papers), pp

Reference 14

Resolution: verified exact; doi, observed 2026-08-06T17:48:38.679029Z

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.

Observation 6d011b18-0c74-4659-afa5-4bb462e804ad · outbound

This paper cites https://python.langchain.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking https://python.langchain

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:48:39.817469Z

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.

Observation 41bf8760-0c4d-488a-b7cd-94c23ef86a8e · outbound

This paper cites In: Proceedings of the 34th Inter- national Conference on Neural Information Processing Systems (NIPS ’20).

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking In: Proceedings of the 34th Inter- national Conference on Neural Information Processing Systems (NIPS ’20)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.818772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fbac7be-dd4f-463e-bdfe-7962fb841f46 · outbound

This paper cites doi.org/10.48550/arXiv.2402.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking doi.org/10.48550/arXiv.2402

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.879510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95baaf08-d18a-4afb-9cd5-560e916fb21c · outbound

This paper cites GPT-4 Technical Report.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking GPT-4 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:37.950755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a8b80ab-ee3a-42dc-a4f6-fcc90011edf0 · outbound

This paper cites Y., Parrish, A., Joshi, N., Nangia, N., Phang, J., Chen, A., Padmaku- mar, V., Ma, J., Thompson, J., He, H., Bowman, S.: QuALITY: Question Answer- ing with Long Input Texts, Yes!.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking Y., Parrish, A., Joshi, N., Nangia, N., Phang, J., Chen, A., Padmaku- mar, V., Ma, J., Thompson, J., He, H., Bowman, S.: QuALITY: Question Answer- ing with Long Input Texts, Yes!

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:38.033456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d286ae63-b63f-4b3c-b6c1-37ed5eb3f51d · outbound

This paper cites doi.org/10.5555/12345678.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking doi.org/10.5555/12345678

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:38.117212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a50cf6e7-0447-4b45-990e-2e2182ec881d · outbound

This paper cites In: Proceedings of ACL 2012 Student Research Workshop, pp.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking In: Proceedings of ACL 2012 Student Research Workshop, pp

Reference 21

Resolution: verified exact; doi, observed 2026-08-06T17:48:38.503655Z

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.

Observation 0492b90b-d46e-49cf-9e73-0e8d3bb20512 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:38.241821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2be618af-6fcf-47eb-8c00-fb55b7082317 · outbound

This paper cites RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval.

Enhancing Retrieval Augmented Generation with Hierarchical Text Segmentation Chunking RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T17:48:38.312580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.