Paper Citation Record · LEDGER

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

As of 18 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 5 inbound Pith citation observations for arXiv:2505.19819.

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

pith.paper-citation-record.v1
2505.19819 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:42.578894Z

measured 56 of 56 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:33:33.242741Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:57:38.031024Z

Reference resolution

51 of 51 outbound references displayed

verified exact0
verified fuzzy37
unresolved14
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d3a5630f-efa8-46a8-914f-ac0177f038c5 · outbound

This paper cites FinTral: A family of GPT-4 level multimodal financial large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets FinTral: A family of GPT-4 level multimodal financial large language models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:49.104361Z

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 6511fbbd-c3f1-46ee-b8ff-c79d0df21df9 · outbound

This paper cites Can GPT models be financial analysts? an evaluation of ChatGPT and GPT-4 on mock CFA exams.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Can GPT models be financial analysts? an evaluation of ChatGPT and GPT-4 on mock CFA exams

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:48.962148Z

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 b1394721-6235-4fa8-b73c-cb0ecf8386d1 · outbound

This paper cites Data-driven detection of subtype-specific differentially expressed genes.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Data-driven detection of subtype-specific differentially expressed genes

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:48.808115Z

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 48f708f6-7515-400e-8b80-c8d323f2c8fd · outbound

This paper cites Adaptformer: Adapting vision transformers for scalable visual recognition.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Adaptformer: Adapting vision transformers for scalable visual recognition

Reference 4

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Source-reported events for the cited work

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Observation 2cd4e657-936d-432a-b872-bf51dbb331f9 · outbound

This paper cites Uncertainty quantification and interpretability for clinical trial approval prediction.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Uncertainty quantification and interpretability for clinical trial approval prediction

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:48.656555Z

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 ca91a882-17ef-4450-86a1-89dd5b064ac8 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Training Verifiers to Solve Math Word Problems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:39.838185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d509754-befa-4dd1-bcec-e4053570fba9 · outbound

This paper cites QLoRA: Efficient finetuning of quantized LLMs.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets QLoRA: Efficient finetuning of quantized LLMs

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:48.500841Z

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 3cb6de15-a6d5-49fa-8ccd-7599685b8626 · outbound

This paper cites The Llama 3 herd of models, 2024.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets The Llama 3 herd of models, 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:48.333186Z

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 e111d828-fd10-4c4c-950a-fc2157e51c7b · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:40.196632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 750c4e1b-4650-4a53-b2d6-94fd2b57cf9f · outbound

This paper cites XBRL Agent: Lever- aging large language models for financial report analysis.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets XBRL Agent: Lever- aging large language models for financial report analysis

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:48.107504Z

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 36631d34-9473-4e9f-b194-384fe6f1e9ac · outbound

This paper cites Measuring Massive Multitask Language Understanding.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Measuring Massive Multitask Language Understanding

Reference 11

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Source-reported events for the cited work

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Observation b5237299-29cd-43ae-abef-6536ea36b51f · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets LoRA: Low-rank adaptation of large language models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:47.922480Z

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 7c5d1168-833d-4c03-a7c4-458efba054c1 · outbound

This paper cites Fine-tuning transformers efficiently: A survey on LoRA and its impact.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Fine-tuning transformers efficiently: A survey on LoRA and its impact

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:47.758912Z

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 d134c0ac-5e20-4273-99a7-3a7af56f917e · outbound

This paper cites GPT-4o System Card.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets GPT-4o System Card

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:40.571087Z

Source-reported events for the cited work

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Observation c83381c5-304b-4843-b517-abc84356098a · outbound

This paper cites FinanceBench: A new benchmark for financial question answering, 2023.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets FinanceBench: A new benchmark for financial question answering, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:47.585218Z

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 20882398-8fbb-4f1f-b422-3ddad6aa2c76 · outbound

This paper cites A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA, 2023.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA, 2023

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:47.406989Z

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 465c7dbb-adc0-4f40-b917-fdf1a7d4a91f · outbound

This paper cites Large language models in finance (finllms).

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Large language models in finance (finllms)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:47.200947Z

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 729ee39c-20aa-4373-84f2-4f1810c0987c · outbound

This paper cites DeepSeek-V3 Technical Report.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets DeepSeek-V3 Technical Report

Reference 18

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Source-reported events for the cited work

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Observation 05e585e6-7c6c-4f9b-957d-894c07c88510 · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:41.062376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3258dce4-fdd1-426d-8d0b-d1045446c97e · outbound

This paper cites SocraticLM: Exploring socratic personalized teaching with large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets SocraticLM: Exploring socratic personalized teaching with large language models

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:47.021204Z

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 7ec16e2a-7dd7-47ee-b0c8-0aaaf433dfd3 · outbound

This paper cites DoRA: Weight-decomposed low-rank adaptation.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets DoRA: Weight-decomposed low-rank adaptation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:46.853122Z

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 262f86d3-3b4c-4226-ade7-df7ed785fb6a · outbound

This paper cites Data-centric FinGPT: De- mocratizing internet-scale data for financial large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Data-centric FinGPT: De- mocratizing internet-scale data for financial large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:46.625114Z

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 797c915c-5902-49e4-a8e6-14f1cb3ce5a3 · outbound

This paper cites Efficient Pretraining and Finetuning of Quantized LLMs with Low-Rank Structure.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Efficient Pretraining and Finetuning of Quantized LLMs with Low-Rank Structure

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:46.491648Z

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 8528b444-4eea-4975-b55f-275485581961 · outbound

This paper cites Zhu, Daochen Zha, J.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Zhu, Daochen Zha, J

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:46.309464Z

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 2e99b5b0-7d6f-4c47-8832-5e7a8ffa9eee · outbound

This paper cites FiNER: Financial numeric entity recognition for XBRL tagging.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets FiNER: Financial numeric entity recognition for XBRL tagging

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:46.106379Z

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 ddc349f9-36a6-467c-8833-9f75bc4f4cb2 · outbound

This paper cites COT: an effi- cient and accurate method for detecting marker genes among many subtypes.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets COT: an effi- cient and accurate method for detecting marker genes among many subtypes

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:45.894364Z

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 a389ca3d-567a-4584-8dc2-88f24eea476f · outbound

This paper cites Www’18 open challenge: Financial opinion mining and question answering.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Www’18 open challenge: Financial opinion mining and question answering

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:45.716392Z

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 a64fe48c-c6f1-4e46-bb27-00293e45f1f5 · outbound

This paper cites Good debt or bad debt: Detecting semantic orientations in economic texts, 2013.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Good debt or bad debt: Detecting semantic orientations in economic texts, 2013

Reference 28

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Source-reported events for the cited work

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Observation 3ba58098-dac2-4e2a-9196-3d033ddc885c · outbound

This paper cites A survey on lora of large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets A survey on lora of large language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:45.548991Z

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 8a797ba5-a284-4735-809d-0213e596b3bb · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:45.345385Z

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 87201375-af03-4d12-a554-80c544b90602 · outbound

This paper cites Pissa: Principal singular values and singular vectors adaptation of large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Pissa: Principal singular values and singular vectors adaptation of large language models

Reference 31

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Source-reported events for the cited work

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Observation 8bedec23-2503-4d87-9113-340ee3bbddac · outbound

This paper cites OpenAI API pricing.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets OpenAI API pricing

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:45.173845Z

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 018c58fc-c2f6-414a-b8b6-db0bfe34b464 · outbound

This paper cites Abdur Rahman.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Abdur Rahman

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.972056Z

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 1ff13f1b-0a0f-4e76-b7a2-f9955444e9b0 · outbound

This paper cites An introduction to XBRL.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets An introduction to XBRL

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.771797Z

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 48ffc979-4fe7-4e46-b590-db2359fd8e47 · outbound

This paper cites Domain adaption of named entity recognition to support credit risk assessment.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Domain adaption of named entity recognition to support credit risk assessment

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.614579Z

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 fc648b19-5170-46ca-b438-62e95669c8c7 · outbound

This paper cites Financial numeric extreme labelling: A dataset and bench- marking.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Financial numeric extreme labelling: A dataset and bench- marking

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.529191Z

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 f9dd62ed-dca8-4ce5-a31f-bc16445b277c · outbound

This paper cites Impact of news on the commodity market: Dataset and results, 2020.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Impact of news on the commodity market: Dataset and results, 2020

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.420011Z

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 43c2ca13-61b0-41f2-8a97-8ca788ba77c6 · outbound

This paper cites Improving loRA in privacy-preserving federated learning.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Improving loRA in privacy-preserving federated learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.266373Z

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 f314dace-0224-417b-bfcf-cd56add068e1 · outbound

This paper cites Gemini: A family of highly capable multimodal models, 2024.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Gemini: A family of highly capable multimodal models, 2024

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:44.018211Z

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 b3a6e000-7ef7-4a2c-a0c6-d86811c052a1 · outbound

This paper cites PrivateLoRA for efficient privacy preserving LLM, 2023.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets PrivateLoRA for efficient privacy preserving LLM, 2023

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:43.599924Z

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 a96eae73-3283-453f-9f6f-7c723133a59a · outbound

This paper cites TWIN-GPT: Digital twins for clinical trials via large language model.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets TWIN-GPT: Digital twins for clinical trials via large language model

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:43.403673Z

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 6a7734a0-f17d-4fb9-ade4-fbc60d005084 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets BloombergGPT: A Large Language Model for Finance

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:42.163647Z

Source-reported events for the cited work

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Observation 62792e65-e642-41f1-9c47-6f86257f3f44 · outbound

This paper cites Knowledge-infused legal wisdom: Navigating llm consultation through the lens of diagnostics and positive-unlabeled reinforcement learning.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Knowledge-infused legal wisdom: Navigating llm consultation through the lens of diagnostics and positive-unlabeled reinforcement learning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:43.256240Z

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 c289c73d-871b-4f28-9607-93aa22408e04 · outbound

This paper cites FinBen: An holistic financial benchmark for large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets FinBen: An holistic financial benchmark for large language models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:43.107008Z

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 4822b7e9-62ad-4e96-b283-7f1fde6fa6c9 · outbound

This paper cites PIXIU: A comprehensive benchmark, instruction dataset and large language model for finance.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets PIXIU: A comprehensive benchmark, instruction dataset and large language model for finance

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:42.987643Z

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 fdc1f753-00d5-4992-bd54-a05100e1fd82 · outbound

This paper cites Low-rank adaptation for foundation models: A comprehensive review, 2024.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Low-rank adaptation for foundation models: A comprehensive review, 2024

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:42.860668Z

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 6479a3f8-dea3-4d78-a845-82562679214a · outbound

This paper cites Enhancing financial sentiment analysis via retrieval augmented large language models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Enhancing financial sentiment analysis via retrieval augmented large language models

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:11:42.755015Z

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 38d8a261-9e56-4be3-9428-6d3114d3568d · outbound

This paper cites Bertscore: Evaluating text generation with bert.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Bertscore: Evaluating text generation with bert

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:42.450931Z

Source-reported events for the cited work

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Observation 43921dde-16db-4461-8fe4-7c51f45f0cfd · outbound

This paper cites A Survey of Large Language Models.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets A Survey of Large Language Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:42.489605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a94fc7d-8f65-4f21-b2fb-7be391047e26 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:42.535067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a6d47fc-5f13-4139-bca7-bc28e7dd7c0b · outbound

This paper cites Large Language Models for Disease Diagnosis: A Scoping Review.

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets Large Language Models for Disease Diagnosis: A Scoping Review

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:42.578894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 1ec95097-0fd9-4211-8f59-a728ac548668 · inbound

Multimodal Financial Foundation Models (MFFMs): Progress, Prospects, and Challenges cites this paper.

Multimodal Financial Foundation Models (MFFMs): Progress, Prospects, and Challenges FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T21:19:59.154922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a33054bd-a2e3-4a1e-9225-0ba9446bc606 · inbound

Point-in-Time Financial RAG with Frozen LLMs and Market-Feedback Adaptive Retrieval cites this paper.

Point-in-Time Financial RAG with Frozen LLMs and Market-Feedback Adaptive Retrieval FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:32:43.903613Z

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 9596a0fa-7725-463d-ba0f-2406a44ce5a8 · inbound

EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents cites this paper.

EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:57:38.032370Z

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 2a653bc0-de73-4415-a241-44863d1ff648 · inbound

MiniCache: Reusable Program Caching with Small Model Interfaces for Efficient LLM Inference cites this paper.

MiniCache: Reusable Program Caching with Small Model Interfaces for Efficient LLM Inference FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:08.181911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32516c05-0ee4-47f5-922e-0d1c91c624a6 · inbound

Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction cites this paper.

Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-16T00:33:33.242741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.