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Paper Citation Record · LEDGER

V-FiLLM: Verified Financial LLM Reasoning Benchmark

As of 12 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=sha256:7ec293e8e1a3ee88ad27bd5f05ffbe0f196865a9f5531ee6afcb7b0cc8cf804d

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:fcd2b04daacf695ccea6f03f3f63307cb91672300203005ec1784239f5360909

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:f29931698a75a6ad299f9460bcc414950f011abfecf18071c4e1358795cbd697

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:b0085d6d8dcc74aebf4055f35a9781156601536422a053cd0e667f260a870c69

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

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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=sha256:8852e43f8d1bdd0900d7a93d7524ec843308b4d434d83ae5f273a9d6c00efdb3

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:b404f666edf31a651f125eb36ecd6680c60a80ecdc11e743ff6a3d6841056045

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.499162Z digest=sha256:a48fd86ee73835427beab1df3902907aea285bf9f45658cc3dd5eff10db7810d

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=sha256:2bb5ad097bac146f97e603e4181081f35da02a0d019be38e5379595728589e24

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=sha256:65f0c515c0b9a128471f2484b438e587e968ff5a541650be1a9bacee3f08c28c

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=sha256:1baa96aff102fc2e03fb382c63d669b2809a48e9986fadc8c6dd3f7606c8bdb5

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=sha256:7c6cc91317409bbd1cb658bdd20e2982bc102a40a957845b64bd0b73b0725e77

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:f7042d29ed0af64a83f540c0450351b8be61c0ec66cf9ad35ec56f3a11c78e1f

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=sha256:8e3204516ab3c354548528a96bd65b19f02d61ed3696685bed01e2908ce5c08b

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

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.533197Z digest=sha256:9ff66e4688e37b3422810b89da83fdc487731cef669eb65e84af158387362df3

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.538468Z digest=sha256:cc7807cc2e4d1f7800c1cacd60d7664b062fc05c850ecce892317b788ef0b0cd

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:af70137048fe424811661f390a155916b61c23a371a863eb29c6154051304ee7

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:c285ddadb30f863b662e6dd42f78e3e3185b05ebfa0590def2dffddb1cd023dd

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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no resolver link, observed 2026-08-12T11:27:14.554690Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.554690Z digest=sha256:2f1c2b21ba3a3214f9fc42ccef4cc55af46745627ac0f7efb1e6da358f758253

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=sha256:5fe48b616a7b96b97e06b9fe16d2555ad6fce992226a6bd99d6cbc3d8a393420

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=sha256:2cec1f9041c26bd0844702517bc3a0af21fc1488f953d240a4f506805a1c1570

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.569773Z digest=sha256:b661f5ed480bb868ea82b0c21031f6b0395eb1b732066bfa903b700869ad699e

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:27:14.574849Z digest=sha256:fb3adb96f36870e2c1bee0d7ebc96278f1c773237d18afdf6a4b7be62c7c7211

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:b0866b07540be1f1cf97fc611f42a1069c536f2111db6d0e7c2c81edc375a127

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=sha256:004625105e43f6b33a7b5b8b4482bfdce1c2eb32054debd389cc76ee2942dafe

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=sha256:90ae97d29e00a698a0529fba004b766ba29614c9be8fa60acc8922f559aa25a3

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=sha256:216bc852c16839b66f548761aaaf245238b9f6b3f42b8553db137edca1c4e9e1

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.600117Z digest=sha256:722a1e3ceaace658975bc604690205bbf4a49857821625fed95598db0e2c86ec

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=sha256:9025fd8b8b42acef3d9ae3b694ff85d5a0ce6b4e0ab58571fdac4365a509d8a5

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=sha256:8cecd3d56713f62781410d471a979f57615a1bca3485a6971140349879dc4b99

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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metadata mismatch
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:eead4841ea273b01aa2faa45de96c34f6bb39e540777ab2ae0f9daf3c140e25c

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-12T11:27:14.620342Z digest=sha256:980e1bd7b637377fc938854cb6d6c7466da5e4f42b0e90fb71a66764777bb5ff

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=sha256:9d3e3a1dd806a8e93692f2b8835a100cc849d7fd2b8d57bb6dabbb094b80caa9

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:be13fa3fce82095e997ca12a9f462ba2a056fa41d9476395f5613cda2da7a5cd

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=sha256:1c6a50942c43d110ff1c9067f9f1e4514226e8b951fec4970fc0c07b607d8e96

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=sha256:1aa3097c52bf532d2ff7ff7cb1fa12d7b0665b4000f7febf0fc32cbd1f3df806

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:c54ad2a7cb0d8f3f93fad075753ccdddb3451232766962c2d10b5cbc2b606919

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=sha256:63bdc0fd34a9ce33cfd87ad8078d3108e1d516c5860ba2f39294842746dcaef9

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:f01eb5a66393b78c28df0670700de46c93aa7884f10f0840e7b643966f36b8f2

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=sha256:15a9a8b4c834cfc1027734024d07473d4a2f9189c6945ec640343a388e64f29d

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=sha256:5d1a9f4fb6ec54050f77555ba64eabe9b38e6be6748b92bb528399ac8b38f893

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=sha256:77765d44c70232fd693a0b40a73256ad113de9d6c982b6b404a55f5808d8f04f

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=sha256:584cdcfe86701056193255d4b9df8c3f27c7cab3da52390c71457b6f1a19a560

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=sha256:35117666462b96ca733e9002a14f899476b79eff62673f38a2769ac375838773

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=sha256:2f1d1f43103c92be5f874da5bacf56ac274a1aec2386ec4d192eac6d038ab420

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=sha256:26767057679a7be6c2a55913eae59fbe0acedb863ed9930dbb3925ccd3176e24

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=sha256:2c9e82f81c073d5ba6dec3c06d350640da587f954e6ab4a67f27560e314a654b

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=sha256:94804ea43cc48522217b37a55aeec4832aa83009ccbf746f178e9b63fa9b717e

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=sha256:350290bd8d5be8a6d8587cb5c5fac88ecd135b10565c3e40a8f9bf6139d982a3

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:bcccae5f8858730dc5aa9861b6a30dcc33b2b327cb513c22398445d274f41d3f

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=sha256:429476db5c760a45ed049fbb554716df6199a905bf882299ada4cdf509ae8df8

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=sha256:0103b13947722e7a8d7cb8caeb27f917dac1585d3e2070b461749093a04e24d4

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=sha256:8ac5e44f314070ab109645b0ca0e104ae91b78c373e7f412786d3883a76d6ffa

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:bcb038c6bfeeedcfb7a37369e6708a0f828419759c2c94a5e47695c1411a700f

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=sha256:11404cfe3581e8f00ca0845b807534b194dabced400608237f32f2439d1fc96d

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=sha256:0a84d94aabb9baa1720a7101ce305fda9b0dd30ae482128b723564e11c4d1a77

Pith citing papers

No inbound Pith citation observations are available.