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Paper Citation Record · LEDGER

V-FiLLM: Verified Financial LLM Reasoning Benchmark

As of 13 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2608.11047.

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

pith.paper-citation-record.v1
2608.11047 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:27:14.740756Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

55 of 55 outbound references displayed

  • verified exact7
  • verified fuzzy5
  • unresolved39
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a82a223f-ce73-4e1a-86c8-524e11e4605b · outbound

This paper cites Royal Society Open Science , author =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Royal Society Open Science , author =

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-12T11:27:15.814555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.465181Z digest=sha256:a336850e9804bfeaab0b96a93215eec53db5daaef39aa53bcbad67c4780f8b75

Observation 18c20d07-9891-43d6-8914-389ee9b160c2 · outbound

This paper cites an unresolved cited work.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.472921Z digest=sha256:f51590b0bcfd090b5d5617261c6b94a57db747946e1fe95e29a8f66cba457f96

Observation d3d4b963-4817-483b-ad8c-f8a3a56859bd · outbound

This paper cites Journal of Financial Data Science , author =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Journal of Financial Data Science , author =

Reference 3

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raw_fallback, observed 2026-08-12T11:27:15.784013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.478110Z digest=sha256:65a0928ba82c43568bbf71fe4a20f921c6a3cd0fb406f9b9eac53333bdd6f5dc

Observation 21207e7a-cb1e-403f-a346-6a4f00d03b27 · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

V-FiLLM: Verified Financial LLM Reasoning Benchmark GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.482978Z digest=sha256:57d53ad28a486bc5180392fac23fa3a1cececd8c063c099e3486c0692adb43f1

Observation 1be2fae3-78d6-474f-b0d8-ca1693951683 · outbound

This paper cites and Schärli, Nathanael and Zhou, Denny , month = jul, year =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark and Schärli, Nathanael and Zhou, Denny , month = jul, year =

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T11:27:15.768285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.488851Z digest=sha256:f9328952492b92c0f0c224b198707167ebc2c9bddcbac9dfec0640f00e44a741

Observation 8a2e1531-9206-4fea-8023-4fd74050eb7a · outbound

This paper cites Proceedings of the 2024.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Proceedings of the 2024

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.494069Z digest=sha256:f5c06383827373056eeb55bf065980c38a75723bfd48baa9777633700bb9f2a3

Observation 11901028-0c03-4170-a2d9-03d864c444ab · outbound

This paper cites Proceedings of the 61st.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Proceedings of the 61st

Reference 7

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source=arxiv_source observed=2026-08-12T11:27:14.499162Z digest=sha256:0034425f355d6ae8d910a7b055e576f7c87141118bd74f0733ef627efc7c89c1

Observation 8275cf26-577b-4e5c-90f2-ee5a54ca28ed · outbound

This paper cites an unresolved cited work.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Unresolved cited work

Reference 8

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parse uncertain
no resolver link, observed 2026-08-12T11:27:14.504228Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.504228Z digest=sha256:3ad897bc31169ff4628d049bd157a6d73d02e7a74442a788b1d5c25bfd6251a2

Observation 638d1d04-55ae-4633-9f53-0766c56e991e · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 9

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source=arxiv_source observed=2026-08-12T11:27:14.508896Z digest=sha256:d58b03e75dd266deafd311e63ef0331dfa9beea53f4ac375fd666c4671dbf073

Observation 6070be9a-045b-4b3d-b50c-a1f8e4f02ad1 · outbound

This paper cites arXiv.org , author =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark arXiv.org , author =

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-12T11:27:15.742432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.514276Z digest=sha256:605abf82a3b39b7be0a28c3c5196793a7ccf5d42b4b6fb9f089b21f7fbeac281

Observation 295d2c15-6841-4434-89b4-817a26a17ff7 · outbound

This paper cites an unresolved cited work.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.519444Z digest=sha256:3e55ed7906bd179a7204750c2716c067d495fd6edf7093d9535f3316e25a8875

Observation d68f7240-e2a6-436b-881e-57c7c7fcb871 · outbound

This paper cites an unresolved cited work.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-12T11:27:14.523907Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.523907Z digest=sha256:700e440375ab39ecd654c85353c6a65113b64270753da9ade1c0f18227ace0ff

Observation 6dc34919-0876-49ad-8c58-b9e45926ec96 · outbound

This paper cites State of.

V-FiLLM: Verified Financial LLM Reasoning Benchmark State of

Reference 13

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source=arxiv_source observed=2026-08-12T11:27:14.528646Z digest=sha256:5fb2311adf7f17995a1aef5bbd978abe8e7544cf037b75b6032634470c7f1777

Observation b1df4501-1674-4086-84be-0c3ad29511a4 · outbound

This paper cites Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning

Reference 14

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no resolver link, observed 2026-08-12T11:27:14.533197Z

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source=arxiv_source observed=2026-08-12T11:27:14.533197Z digest=sha256:c6bd279786180f8d2785a3d226d0744213ea9ffc75ce8de9f0effe74a879c45b

Observation 2e070690-7432-4f89-9411-eadca9a51fac · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

V-FiLLM: Verified Financial LLM Reasoning Benchmark LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 15

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no resolver link, observed 2026-08-12T11:27:14.538468Z

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source=arxiv_source observed=2026-08-12T11:27:14.538468Z digest=sha256:ec3481864d936bed9b1c6b33f2a48304bb2a69f28cdf1e520d75c19f86fa5d2e

Observation 9a7d4f31-e938-485a-b948-ddb02759a5a4 · outbound

This paper cites Parameter-Efficient Transfer Learning for NLP.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Parameter-Efficient Transfer Learning for NLP

Reference 16

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source=arxiv_source observed=2026-08-12T11:27:14.543528Z digest=sha256:2af7ded3da5ee2db8f4403d27bcf6976dc58d07c705a0473b4c4d58e3d5dc01d

Observation 1fa46fb9-7413-44e4-8bdf-539da2ea1bae · outbound

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

V-FiLLM: Verified Financial LLM Reasoning Benchmark LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

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source=arxiv_source observed=2026-08-12T11:27:14.548592Z digest=sha256:53b5e7364466b2cc66c073000af2d6688f1e7e54178eba0969f41be142923190

Observation f8aa8649-599e-4745-9a40-a696840490cf · outbound

This paper cites Faith and Fate: Limits of Transformers on Compositionality.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Faith and Fate: Limits of Transformers on Compositionality

Reference 18

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source=arxiv_source observed=2026-08-12T11:27:14.554690Z digest=sha256:59a5b81912fa7e96ca7662a242eeb2ab88c7ca8cf3019360439a0208d1579088

Observation 8cfed1da-fdef-44d5-9985-0b5c4f905fae · outbound

This paper cites Compositional.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Compositional

Reference 19

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source=arxiv_source observed=2026-08-12T11:27:14.559559Z digest=sha256:06323459697ad54ca815f13610cf282ac747be458a240b4ff7608c638a74f1c2

Observation dd3966e0-d8c0-4322-870a-048d2854dae9 · outbound

This paper cites Findings of the.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Findings of the

Reference 20

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source=arxiv_source observed=2026-08-12T11:27:14.564906Z digest=sha256:1333b5644f6080a0b4eb1b1883a09c6aba187cc3bde9f2017404372a5c3ef531

Observation 91bf9fc0-82d3-427b-aa8d-ebad0bdf38b9 · outbound

This paper cites DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks.

V-FiLLM: Verified Financial LLM Reasoning Benchmark DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks

Reference 21

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source=arxiv_source observed=2026-08-12T11:27:14.569773Z digest=sha256:6b3837043c2e38d0810098c8d62450b5607ed9d6c94f943a7a60c8adb442ebd6

Observation 24d6dea3-d680-4ed2-ad79-01097e3172ee · outbound

This paper cites BizBench: A Quantitative Reasoning Benchmark for Business and Finance.

V-FiLLM: Verified Financial LLM Reasoning Benchmark BizBench: A Quantitative Reasoning Benchmark for Business and Finance

Reference 22

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-12T11:27:14.574849Z digest=sha256:332c04daf68877cc9273c5951d3738044c344653b44916352c29aeaf2356e125

Observation 7f11c845-30cd-4694-ad99-33752ee8ad1e · outbound

This paper cites MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data.

V-FiLLM: Verified Financial LLM Reasoning Benchmark MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data

Reference 23

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source=arxiv_source observed=2026-08-12T11:27:14.579823Z digest=sha256:eaf793e6cee938302be8f72f9aeccc47a9263295aabd0792ebc9bea6e67b3410

Observation ce0b6129-7434-4486-baee-307b062af219 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

V-FiLLM: Verified Financial LLM Reasoning Benchmark GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 24

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source=arxiv_source observed=2026-08-12T11:27:14.584718Z digest=sha256:02961c4bbb317b4524366dccd4e917c927dcdce72fa7946157fc9fe7cfce1261

Observation d8e4b936-32ed-49d7-8968-d03e5810c415 · outbound

This paper cites Findings of the.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Findings of the

Reference 25

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source=arxiv_source observed=2026-08-12T11:27:14.590042Z digest=sha256:25888f054f252695eb1cf71d7954b29848777379e8c261a8b1aba17c4d767a4e

Observation a4c2a1a7-ee44-4d37-8fbb-5b987b6af374 · outbound

This paper cites TabFact: A Large-scale Dataset for Table-based Fact Verification.

V-FiLLM: Verified Financial LLM Reasoning Benchmark TabFact: A Large-scale Dataset for Table-based Fact Verification

Reference 26

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source=arxiv_source observed=2026-08-12T11:27:14.594944Z digest=sha256:32128d2d7452f7941b6f8cb0d9b99a9890cbe0bc3412b48da7384ad98cb27899

Observation f1adfcf5-f805-47ce-beca-cfd2b880a6bb · outbound

This paper cites doi:10.48550/arXiv.2509.25160 , abstract =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark doi:10.48550/arXiv.2509.25160 , abstract =

Reference 27

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verified exact
doi, observed 2026-08-12T11:27:15.425169Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.600117Z digest=sha256:f28617587159192997d453da81dfed6a596af0c130643444bdcc141e2ddc8947

Observation e3a3cd35-f541-4820-a96e-53553c5be3c1 · outbound

This paper cites DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.

V-FiLLM: Verified Financial LLM Reasoning Benchmark DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Reference 28

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source=arxiv_source observed=2026-08-12T11:27:14.604742Z digest=sha256:d23df92c22c46d0039b40aa1c203a0bf2bf3f5007771c54b87fecae464d1194a

Observation 42a7500a-9b27-4ba5-b9bb-d96447bfe60d · outbound

This paper cites TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance.

V-FiLLM: Verified Financial LLM Reasoning Benchmark TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance

Reference 29

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source=arxiv_source observed=2026-08-12T11:27:14.609994Z digest=sha256:d3048b466b69dc449b59916a49af3794502ed5f2672ef90f8fef6181d9a8118c

Observation 8500b8c7-4524-488f-aecf-0c407067f575 · outbound

This paper cites DORO: Distributional and Outlier Robust Optimization.

V-FiLLM: Verified Financial LLM Reasoning Benchmark DORO: Distributional and Outlier Robust Optimization

Reference 30

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local_arxiv, observed 2026-08-12T11:27:15.309985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.615115Z digest=sha256:06080645b6ca38d2e76657ca0fe61508878b46591e3579dc5e818d8092d97fc6

Observation 17ebcb4b-0bde-442b-839a-eb79b1d79672 · outbound

This paper cites and Haghgoo, Behzad and Chen, Annie S.

V-FiLLM: Verified Financial LLM Reasoning Benchmark and Haghgoo, Behzad and Chen, Annie S

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-12T11:27:15.710880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.620342Z digest=sha256:94c92dcd3c486d2c4de9a6012495fa58ca2fa6a0ce4be0338950a540849a1c6a

Observation 893c57f4-7fcf-481f-8125-1d612ac6cda5 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 32

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source=arxiv_source observed=2026-08-12T11:27:14.625334Z digest=sha256:855be60834c8a48724eddd2df6ac745427c71e06f04c2943aa20e0432dc1d4fe

Observation c5b2f6bc-9153-46e8-b5f2-fa4d890b401a · outbound

This paper cites Evaluating.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Evaluating

Reference 33

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source=arxiv_source observed=2026-08-12T11:27:14.630485Z digest=sha256:00f274a30f0b2dc7fd587a8181c9cfc7167c05c4f43ca9cda2b7dfdc1e714234

Observation 6a11c748-9428-41a6-be10-d3b0609dc4f5 · outbound

This paper cites Enabling.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Enabling

Reference 34

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source=arxiv_source observed=2026-08-12T11:27:14.635401Z digest=sha256:da38cf76423dd9620bdaadaa9efced3cafdb183713f485d0150462ecd80fc0bf

Observation 70fd02e5-b0f8-4348-a893-5c06c9662ec1 · outbound

This paper cites Measuring.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Measuring

Reference 35

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source=arxiv_source observed=2026-08-12T11:27:14.640336Z digest=sha256:a91207af19211e9cedab03a18e0b860876053b0209e88291a30534c403dbba11

Observation 435d29ca-81d3-40cf-8d41-72191df3d903 · outbound

This paper cites Advances in Neural Information Processing Systems , author =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Advances in Neural Information Processing Systems , author =

Reference 36

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source=arxiv_source observed=2026-08-12T11:27:14.645389Z digest=sha256:1d0f993dc5358ede2019f34dca362f9b40fa3465107a0e7e6785a20f03686059

Observation 6ae0a78c-693f-4c9c-a4ba-6c5ab9043d4e · outbound

This paper cites DeepSciVerify: Verifying Scientific Claim--Citation Alignment via LLM-Driven Evidence Escalation.

V-FiLLM: Verified Financial LLM Reasoning Benchmark DeepSciVerify: Verifying Scientific Claim--Citation Alignment via LLM-Driven Evidence Escalation

Reference 37

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local_arxiv, observed 2026-08-12T11:27:15.239546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.649731Z digest=sha256:d1bf21400fb14dbd34a17e4d2dcd6ebd6a35adc81d159144ce06445da77d6d7e

Observation 0786b739-323b-406d-81cf-1a8b92555a4d · outbound

This paper cites Evaluating Large Language Models at Evaluating Instruction Following.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Evaluating Large Language Models at Evaluating Instruction Following

Reference 38

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unresolved
no resolver link, observed 2026-08-12T11:27:14.654832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.654832Z digest=sha256:978d251fb6552a7b00e8805208f266139bb6848f58ec6a4fcf3b3323e2c289fa

Observation 04ce2feb-6030-4475-83fc-3616d40e9a35 · outbound

This paper cites Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.659813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.659813Z digest=sha256:ba5463b20a490631963284de39a2cbca2c2c09e05f8185400a21affd466b09da

Observation 372cb7e0-17b5-4fbf-9a42-f20d3b8c57c3 · outbound

This paper cites an unresolved cited work.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Unresolved cited work

Reference 40

Resolution
verified exact
doi, observed 2026-08-12T11:27:15.181180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.664613Z digest=sha256:e6079653a1d40fc8d364ed58a4705beeff59b50ca8427262b7dae2bce1e42556

Observation 28a4c5a3-e92b-42c4-953e-6024c09ca0c6 · outbound

This paper cites Proceedings of the 63rd.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Proceedings of the 63rd

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.669429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.669429Z digest=sha256:492b59295cfaf71c4e5593f77d128db9c8a0c55ed31da2ae059c38ab40666836

Observation 3e170810-b0cb-4fdf-893b-cedca4f5aa9b · outbound

This paper cites an unresolved cited work.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Unresolved cited work

Reference 42

Resolution
verified exact
doi, observed 2026-08-12T11:27:15.100351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.675157Z digest=sha256:cc8acd183a0a248b2fc9302d676da8b3b24aea4fe63638ea7f6177e753fd6ed5

Observation a744e5b3-94de-4f9c-abd5-b48e66509e8b · outbound

This paper cites On the Limits of LLM-as-Judge for Scientific Novelty Assessment.

V-FiLLM: Verified Financial LLM Reasoning Benchmark On the Limits of LLM-as-Judge for Scientific Novelty Assessment

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.679948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.679948Z digest=sha256:9c972c124a9cbdd8cebbbb2dda6a3a25084fd3e8282ecd46c670f1d402aacfbe

Observation 25cb44d5-be12-404e-bdc6-331dd3e08d6b · outbound

This paper cites and Goel, Pranav and Stoehr, Niklas and Ash, Elliott and Hoyle, Alexander Miserlis , editor =.

V-FiLLM: Verified Financial LLM Reasoning Benchmark and Goel, Pranav and Stoehr, Niklas and Ash, Elliott and Hoyle, Alexander Miserlis , editor =

Reference 44

Resolution
verified exact
doi, observed 2026-08-12T11:27:14.973197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.684978Z digest=sha256:f305c16b79064e1ca2e5aa8361dc5148f7ddabe031a10bd74250ffd6c34df51d

Observation c4fff4a4-17d5-4146-894e-98057756c811 · outbound

This paper cites Cited but Not Verified: Parsing and Evaluating Source Attribution in LLM Deep Research Agents.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Cited but Not Verified: Parsing and Evaluating Source Attribution in LLM Deep Research Agents

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.690819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.690819Z digest=sha256:516dec130238bee4f713286ad023ff614a3dee09977ce304927f389de9364968

Observation 9743ab4e-951d-4903-8156-94fb349244f4 · outbound

This paper cites AURA: Adaptive Uncertainty-aware Refinement for LLM-as-a-Judge Auditing.

V-FiLLM: Verified Financial LLM Reasoning Benchmark AURA: Adaptive Uncertainty-aware Refinement for LLM-as-a-Judge Auditing

Reference 46

Resolution
metadata mismatch
local_arxiv, observed 2026-08-12T11:27:14.941244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.695950Z digest=sha256:0bdb15b2f6bc695a01f5c2096bd4cb14df1dbb3da637965446e1d4dc4be6de4b

Observation c487bd08-d28b-4bf6-966a-6ce5fbfbb600 · outbound

This paper cites Rethinking Literature Search Evaluation: Deep Research Helps, and Human Citation Lists Are Not a Ground Truth.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Rethinking Literature Search Evaluation: Deep Research Helps, and Human Citation Lists Are Not a Ground Truth

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-12T11:27:14.919387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.700894Z digest=sha256:f4d136fb2a97ae069ff42fa258e7db29e5ff0c5b03e89ba7643fcc12fc2fb448

Observation 71e4d072-acbd-4332-aee2-764f35a263fd · outbound

This paper cites Citation Grounding Measures the Oracle: Graph Coverage Determines Reported LLM Hallucination Rates in Law.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Citation Grounding Measures the Oracle: Graph Coverage Determines Reported LLM Hallucination Rates in Law

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-12T11:27:14.897265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.705829Z digest=sha256:c331c9c02e5b06120d61ebd6509e26d20fa35f31ac240c5e4c455b21a533997a

Observation a5c890be-981e-49d4-b186-c5aec3ffd088 · outbound

This paper cites LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.

V-FiLLM: Verified Financial LLM Reasoning Benchmark LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.710985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.710985Z digest=sha256:04304d45344746f2dc74f1339e8e4cf859a5542c819ce6f8e484ec494044c300

Observation 6f21bfed-a74f-4d0c-bbe5-4c08ef2704e8 · outbound

This paper cites Findings of the.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Findings of the

Reference 50

Resolution
verified exact
doi, observed 2026-08-12T11:27:14.858172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.716472Z digest=sha256:7085dbd2a7ffc03e8ed7a4c729bd8b3273d1ef96a8ce5e968902aafb055ed92f

Observation b9d8cbf2-89a2-4078-8134-c665b339f574 · outbound

This paper cites FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets.

V-FiLLM: Verified Financial LLM Reasoning Benchmark FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.721155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.721155Z digest=sha256:c68ebbc11ea94987952902926ed6797f0ff0f30065e2b14496cdd0d6a3b28b58

Observation 3e500578-578c-4cfb-892c-0023d18ce1c8 · outbound

This paper cites FinanceBench: A New Benchmark for Financial Question Answering.

V-FiLLM: Verified Financial LLM Reasoning Benchmark FinanceBench: A New Benchmark for Financial Question Answering

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.726217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.726217Z digest=sha256:9e8278602a0e7363e1ded4b76a8bacb0086c8d0208c1cc80e0cc5df5edab2478

Observation df4e0999-fe47-4441-a68f-e71cba2bccb3 · outbound

This paper cites Beyond Knowledge to Agency: Evaluating Expertise, Autonomy, and Integrity in Finance with CNFinBench.

V-FiLLM: Verified Financial LLM Reasoning Benchmark Beyond Knowledge to Agency: Evaluating Expertise, Autonomy, and Integrity in Finance with CNFinBench

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.730913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.730913Z digest=sha256:653db0713cc42e1f46c1d86d002aeb5904e22e79fc59f3fc40421d0cf45d48a6

Observation 788d2f23-0e55-4f54-9dbb-b24f9e08b1af · outbound

This paper cites ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering.

V-FiLLM: Verified Financial LLM Reasoning Benchmark ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.735752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.735752Z digest=sha256:93177ef01f6869f8985a811a409f3f89fba30e5905c98c5b0f0052ea70aea113

Observation 1e72da66-2209-4f13-bfee-8d4b5c18002b · outbound

This paper cites FinQA: A Dataset of Numerical Reasoning over Financial Data.

V-FiLLM: Verified Financial LLM Reasoning Benchmark FinQA: A Dataset of Numerical Reasoning over Financial Data

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T11:27:14.740756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.740756Z digest=sha256:e1c085beda123c2a6cfed1931d10eb80ef76e6d75a69d7214af98fc6c0f773b5

Pith citing papers

No inbound Pith citation observations are available.