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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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.465181Z digest=sha256:6ed9650c91bc5acda490f283011e310fdcb0a306e871f552f4931990e9aede5c

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.472921Z digest=sha256:f7ef582e0b863eb3c47cf48465805c0a0be5564595537006d3eac28ce6e69392

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.478110Z digest=sha256:d558b7d29848816eb838f933978a3bcf391457766ebe9f29892e0e21ff8e63d1

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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no resolver link, observed 2026-08-12T11:27:14.482978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.482978Z digest=sha256:ee083e34fc2db36fa0087f2deb602820e28eecef4060f9d89d2b7b46f8550a94

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.488851Z digest=sha256:b5632236a0fe6eecb42681feb918efbe1ef3b1bbebebd5eb6ea889d369114e29

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:d1a58a6ec81da6b66457cf0125a7740f52ce52d391dd98e64c59e10f75edb697

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=sha256:5672809965e42221261e8155b23baceb1be93751725ef4e9044ce60c79c15f96

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

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source=arxiv_source observed=2026-08-12T11:27:14.504228Z digest=sha256:bacae62a5c143ffc41b2f71e3e3d8834b27ba75c3f6875b84efeb79e77489237

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:aa447439f1161ffd6574c5547d7478b2a14b95380594293224fe96246b091b20

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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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.514276Z digest=sha256:b24631309de01ae9a4e0f254f985997dc86e0dcb9e4a4c5c8b8abab7db6e4f1b

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.519444Z digest=sha256:473fdc1682f2f55f143d5b2ecd5ba6248d2e77479d44e7b8986767e0acd9d9af

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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source=arxiv_source observed=2026-08-12T11:27:14.523907Z digest=sha256:177b0452f653602662fc580d2ccd70ff673741665fdb604c636b1b46b1942cc5

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:eced23ddab1fe4365c361e7ce95a2d9e67ddde5991f0eb4ddb9a65a08019f2ad

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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source=arxiv_source observed=2026-08-12T11:27:14.533197Z digest=sha256:e20f66951a00498b21830af1e286a40f53925d356cd3a185f1287e278efd0b90

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.538468Z digest=sha256:7cbed0ca5dcf5c68baf5e0ae8d67489d245d741502b1b5fddda6e83ebcf0975d

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:fe0336717f70d4b391a993ee39c331db97c625f343c4bce3dfc188cddd48b0fa

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=sha256:29e8bdc1b31328342fd67a828264102b748d76157393127606cb206b46860da0

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.554690Z digest=sha256:757ae114b0ead9415010c924912bef08eaf932aac0029692530152bfa34679ba

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=sha256:29e6787d15bd39435cab74c7bed40f034c068e2ba4fb66ea5eacdb7bf365a41a

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=sha256:9e01b67a49f99f13ff2d9decb75f6e09c5c67918ed90ed83103d8f6eeaa34310

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.569773Z digest=sha256:94dc7d86e9e856098a8157e273f062134dcfccb2bcf45a192c238d635077b0c6

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=arxiv_source observed=2026-08-12T11:27:14.574849Z digest=sha256:d9fe663511b4880d1d83b3061a062022ef77775d971ae9447869603c90cafe64

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:cc16b55ca16cf2beff7957abc9f3e66bc85626ffc43248994dce4b072d51c4cb

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=sha256:7b943e93a979d081f502ca256cc23860eb3057c54b5fa53f32c36bad1b19ab48

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=sha256:3a02648cd08ef9aae72d6c854bdb40675f84d4b95bcd97e1614cfb5818bcbccc

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:f7c16cedffb8c12ebeaa1913cb43aec7bab398c6a21fd39154c3f57dd6fac966

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.600117Z digest=sha256:7552b387c72ab7e1bd46c0d61003b407b749f61d9e4f0713bc65a4b2d8b8488c

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=sha256:51a964df80b8de0e23ed0267285df4e465bd5b023b71ce885596b22964b34146

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=sha256:4ed9523fc857c5983f315fec1084b0901704e17b36f4babcc608a57d9e677a16

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.615115Z digest=sha256:491cdc54bd72f63fa9d2e385c40d4ab80fdaaecb53e8953c42ce2d733c8ea7ed

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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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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.620342Z digest=sha256:33163355e7ee96a69dc6f5fa8ce66c5faaaf3cb0cf417b13743e6449ce955323

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:e642b0fdbce2b669e7a381d48494990c2b48ac6a811da18ac1a692e24b9e7d63

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:eac0a0acdde2d878e840b47205aa01bf4abaf875bb3ac31829d10d775b873896

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=sha256:3fc569db5893b32bdc5c51e24aeea9ae3675df7910b7b279cb257d10a54b9c49

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=sha256:6de636ebb87d74552bdb6991365e5397a2007ada247e311ff499ac0687d61c28

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:a7d36803b35556ed00027df9eb154cac7838db82dcaaa136980a8007126e9b66

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.649731Z digest=sha256:71dc231d70a124d71e87f11e0cbb5371521adc8a62ddb6a6972d4d401ce1cca6

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=sha256:08eaf723aed729c4f9b9c345014b326abdf985c7143effaebd7d1ee74be45440

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:c70d01f661324099bb1062e0d6c3dd3634b9430ddc98e09df1e0a36dcfa5c222

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.664613Z digest=sha256:33d9331eaf53200a3677e0fb0e813c8eb144ac0e4222e052a4093a12fffad2e8

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:cea15c41680024cc2a38a711f47182a3a0f75d83b1a93084252519b8d4b33706

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.675157Z digest=sha256:0b78dba0463f035fe7580303e3f2d5447d0e96e7c23404eb16ee882c5a05c956

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=sha256:3f88a2db2ef9c010fbd44a368fe1769bdff1106b2559b2c6b97a2d2a8eb85d3d

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.684978Z digest=sha256:48d3741db268b8b5e896e192333a90511f05e4cdae1decb1efe1eb3f4d288a71

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:ff2ebd0ee358cf93b1efd456b23232a7fc7b41e8a5dc0cf0267c475cd52985a3

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.695950Z digest=sha256:907a96eca62abcf5de967c0303e6d295121d26302c9a559dbf63a7c936d26b56

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.700894Z digest=sha256:be0178d83f45f664e7cd892ebdee429c758cae800e05d70fee413959fbc4aff4

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.705829Z digest=sha256:840d38df6f34207bfaa79157dd1a08de8b0f7a2e7f218814da49db484b52a185

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=sha256:71ebcc2416c0bf50da9e114e72788ee208e1d35938d9096226983f5c077edd10

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 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.716472Z digest=sha256:50efb99ff3f399ea096afac6e8b6804f96bbd50011e400dd65c270f7724b04b9

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:aad2d5ddbc257036dc20b099aaf33f2af51587d6aac57a1b8b38159d767da7c8

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=sha256:9fdbde8bad0f28736d299edf9cdf671b0a1050e2cf168815fdadc68142b81e50

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=sha256:2679f9e1d0e87566af22567efe6c1f84205629b2262fb2398e5a16a21044dfd3

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=sha256:62c1c1c8ee6285e29b0fdbd1a2757f2e64a0fbb422fd53f16778431e2cfe29c0

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=sha256:6d7d086ecad8538b1875509ad7cbc02becd27432965aafcda9531836ef410c32

Pith citing papers

No inbound Pith citation observations are available.