Paper Citation Record · LEDGER

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation

As of 19 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.08827.

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

pith.paper-citation-record.v1
2506.08827 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:05:59.424449Z

measured 18 of 18 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

18 of 18 outbound references displayed

verified exact0
verified fuzzy2
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 20beb173-e755-480e-a733-b9ddad80f499 · outbound

This paper cites Text Segmentation based on Semantic Word Embeddings.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Text Segmentation based on Semantic Word Embeddings

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.351233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe08efd2-f493-40b3-a508-46953632799a · outbound

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

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.356387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe9f3e46-f8f0-46ae-b62d-20bfb731999b · outbound

This paper cites an unresolved cited work.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:59.776425Z

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 c1a5786d-1df7-46bb-bc65-d2c87d846bfa · outbound

This paper cites How is ChatGPT's behavior changing over time?.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation How is ChatGPT's behavior changing over time?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.364941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cde9899d-7024-4037-8035-5b54db01cb9a · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation QLoRA: Efficient Finetuning of Quantized LLMs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.369616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a606e839-4045-420d-891f-373095f0e775 · outbound

This paper cites The Faiss library.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation The Faiss library

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.374113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a67f5d3-f6f7-412c-8710-1235a7c636f0 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation LoRA: Low-Rank Adaptation of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.378902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20e6dd87-25f8-4d83-b4e3-645ad7256a9b · outbound

This paper cites A Comprehensive Evaluation of Quantization Strategies for Large Language Models.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation A Comprehensive Evaluation of Quantization Strategies for Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.383270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4a5212-8d7a-4d53-b4a3-2962d53ded57 · outbound

This paper cites MatSciRN: Other Electronic (2011), https://api.semanticscholar.org/CorpusID:9633141.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation MatSciRN: Other Electronic (2011), https://api.semanticscholar.org/CorpusID:9633141

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:59.762990Z

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 08243fc3-7c20-4000-b9b1-efde630f05e8 · outbound

This paper cites Large Language Models are Zero-Shot Reasoners.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Large Language Models are Zero-Shot Reasoners

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.392120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1abc45ed-6471-4fd9-900a-7cb763df885d · outbound

This paper cites an unresolved cited work.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:59.749331Z

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 f8c5abbd-dc56-458e-84e3-c9a879c8139e · outbound

This paper cites an unresolved cited work.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:59.736893Z

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 68292b4a-e8fb-4b75-9162-37ba374ece7d · outbound

This paper cites Natural Language Processing Journal6, 100056 (2024).

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Natural Language Processing Journal6, 100056 (2024)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.404832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc811296-3b0b-4160-ad7f-16f8910f56ed · outbound

This paper cites an unresolved cited work.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:59.724496Z

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 2be41ab9-9a90-46a0-9417-58606f9d366c · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.412471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be0d72ab-008f-4ee8-aad1-3174119f66e0 · outbound

This paper cites In: Hassanien, A.E., Bhatnagar, R., Darwish, A.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation In: Hassanien, A.E., Bhatnagar, R., Darwish, A

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:59.711806Z

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 5c76f4cd-e27e-4b94-9efa-e569534d6627 · outbound

This paper cites A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.420504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29f40be2-71cb-4a0b-99b4-04b7d9aa85db · outbound

This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

The impact of fine tuning in LLaMA on hallucinations for named entity extraction in legal documentation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:59.424449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.