Paper Citation Record · LEDGER

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning

As of 21 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.07742.

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

pith.paper-citation-record.v1
2608.07742 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:22:04.590968Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

34 of 34 outbound references displayed

verified exact4
verified fuzzy10
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d2c2178e-d379-4a56-897d-87886bdf3e79 · outbound

This paper cites MVTamperBench: Evaluating Robustness of Vision-Language Models.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning MVTamperBench: Evaluating Robustness of Vision-Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.429523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95930af6-152d-4847-b574-9db3ec94d04c · outbound

This paper cites Introducing claude opus 4.7.https://www.anthropic.com/ news/claude-opus-4-7, 2025.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Introducing claude opus 4.7.https://www.anthropic.com/ news/claude-opus-4-7, 2025

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.378432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4c94f25a-33c2-4698-959f-ee90b9dc19d3 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.440754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b932f388-47a0-4804-ac2d-41960520aa31 · outbound

This paper cites A Causally Grounded Taxonomy for Image Degradation Robustness Evaluation.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning A Causally Grounded Taxonomy for Image Degradation Robustness Evaluation

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-11T00:22:05.182052Z

Source-reported events for the cited work

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Observation 53cb5de0-1ae7-4706-acb0-8c3b05b38293 · outbound

This paper cites Are We on the Right Way for Evaluating Large Vision-Language Models?.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Are We on the Right Way for Evaluating Large Vision-Language Models?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.452206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad1aca39-c351-47cf-b3b5-d0434f2eff2f · outbound

This paper cites Internvl 2.0: Scaling up vi- sion foundation models and aligning for generic visual-linguistic tasks.arXiv preprint arXiv:2403.20377, 2024.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Internvl 2.0: Scaling up vi- sion foundation models and aligning for generic visual-linguistic tasks.arXiv preprint arXiv:2403.20377, 2024

Reference 6

Resolution: verified exact; raw_fallback, observed 2026-08-11T00:22:05.141286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a97dc704-e90e-44dc-8ce7-65813d6950c3 · outbound

This paper cites Evaluating large language models on multimodal chemistry olympiad exams.Communications Chemistry, 8(1):402, 2025.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Evaluating large language models on multimodal chemistry olympiad exams.Communications Chemistry, 8(1):402, 2025

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.363918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b2ce3a9-5fb5-4169-a1ef-6bf59d01f2c0 · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.467478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d6e35fd-5613-486b-a416-a173a01a4d8e · outbound

This paper cites Interpretable explanations of black boxes by meaning- ful perturbation.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Interpretable explanations of black boxes by meaning- ful perturbation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.348717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e652fded-c6a9-4ec3-b0b0-86b3dadf5bcc · outbound

This paper cites Can llms solve molecule puzzles? a multi- modal benchmark for molecular structure elucidation.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Can llms solve molecule puzzles? a multi- modal benchmark for molecular structure elucidation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.333869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 26d8f4cb-3c24-40e4-89a5-93569dda0e23 · outbound

This paper cites Benchmarking neural network robustness to common corruptions and perturbations.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Benchmarking neural network robustness to common corruptions and perturbations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.481013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef188135-90db-4fc3-a947-f7e27123e080 · outbound

This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.308149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f5854e3c-71a6-4a23-a0e6-f5033ddecc6d · outbound

This paper cites Azam Hossain.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Azam Hossain

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.292014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d0af0bd5-dea9-481a-9b50-1c8f3c83cac4 · outbound

This paper cites R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.495381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0098da10-e48e-43a8-9de7-599864049e0d · outbound

This paper cites Chemvlm: Exploring the power of multi- modal large language models in chemistry area.Proceedings of the AAAI Conference on Artificial Intelligence, 39(1):415–423, 2025.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Chemvlm: Exploring the power of multi- modal large language models in chemistry area.Proceedings of the AAAI Conference on Artificial Intelligence, 39(1):415–423, 2025

Reference 15

Resolution: verified exact; doi, observed 2026-08-11T00:22:04.644027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 85f248a5-858a-48f9-bcc3-d370819b4ea8 · outbound

This paper cites Visual Instruction Tuning.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Visual Instruction Tuning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.506537Z

Source-reported events for the cited work

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Observation 5584204e-c1bd-4dcd-a092-3d9174aecb7c · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning MMBench: Is Your Multi-modal Model an All-around Player?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.511776Z

Source-reported events for the cited work

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Observation 47588bda-591d-4116-98bc-d4175c502554 · outbound

This paper cites Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.517161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dfdbbf5-8fc0-4b72-990c-e7b194955a24 · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.522159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad7d8a6d-3b48-421f-a532-f1f232fc1739 · outbound

This paper cites mmjee-eval: A bilingual multimodal bench- mark for evaluating scientific reasoning in vision-language models.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning mmjee-eval: A bilingual multimodal bench- mark for evaluating scientific reasoning in vision-language models

Reference 20

Resolution: verified exact; raw_fallback, observed 2026-08-11T00:22:04.958916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ae810fe8-ed84-4f30-9a5c-15c081bdcd9a · outbound

This paper cites Introducing gpt-4.1 in the api.https://openai.com/index/ gpt-4-1/, 2025.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Introducing gpt-4.1 in the api.https://openai.com/index/ gpt-4-1/, 2025

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.276614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a043a968-b2b9-4adb-9371-169fae5d25ce · outbound

This paper cites Do CIFAR-10 Classifiers Generalize to CIFAR-10?.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Do CIFAR-10 Classifiers Generalize to CIFAR-10?

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.537137Z

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Unavailable: canonical work link unavailable.

Observation 19206fae-4e83-4bcb-90c0-714749c364bd · outbound

This paper cites Do im- agenet classifiers generalize to imagenet? InProceedings of the 36th International Conference on Machine Learning (ICML), pages 5389–5400, 2019.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Do im- agenet classifiers generalize to imagenet? InProceedings of the 36th International Conference on Machine Learning (ICML), pages 5389–5400, 2019

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.261447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 54f65b16-072d-4f54-97cd-1be53ffdd9ca · outbound

This paper cites Hughes, and Finale Doshi-Velez.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Hughes, and Finale Doshi-Velez

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.545977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f78ca4bf-ed1a-44c6-8375-123c8477604f · outbound

This paper cites Assessing the Chemical Intelligence of Large Language Models.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Assessing the Chemical Intelligence of Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.550184Z

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Unavailable: canonical work link unavailable.

Observation 07456421-f0e8-44e1-9d45-071a8e7143ef · outbound

This paper cites Diagnosing Corruption-Induced Reliability Failures in Vision-Language Models.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Diagnosing Corruption-Induced Reliability Failures in Vision-Language Models

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T00:22:04.827239Z

Source-reported events for the cited work

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Observation 40a5ba18-a700-41ea-bf30-4ae401245be8 · outbound

This paper cites Qwen2.5-VL Technical Report.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Qwen2.5-VL Technical Report

Reference 27

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Source-reported events for the cited work

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Observation 0a276d57-6442-4410-84f5-be29e78194bc · outbound

This paper cites Analysing the Robustness of Vision-Language-Models to Common Corruptions.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Analysing the Robustness of Vision-Language-Models to Common Corruptions

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.563578Z

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Unavailable: canonical work link unavailable.

Observation a96f37fe-5b51-49f6-87a8-ea937988ae74 · outbound

This paper cites CogVLM: Visual Expert for Pretrained Language Models.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning CogVLM: Visual Expert for Pretrained Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.567756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07d465fc-27e1-4480-811c-90c38daa5dfe · outbound

This paper cites Demystifying the Visual Quality Paradox in Multimodal Large Language Models.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Demystifying the Visual Quality Paradox in Multimodal Large Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.572242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb975c57-f16a-4c30-a27b-72585bf68f82 · outbound

This paper cites Mmt-bench: A comprehensive multi- modal benchmark for evaluating large vision-language models towards multitask agi.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Mmt-bench: A comprehensive multi- modal benchmark for evaluating large vision-language models towards multitask agi

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.245806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0753f46d-0fcb-4275-927e-8405c2c125d0 · outbound

This paper cites MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.581233Z

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Observation 8f6dd67a-5f3c-498f-bc8d-a8930749ca5f · outbound

This paper cites Zeiler and Rob Fergus.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Zeiler and Rob Fergus

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:22:05.230308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4df0552e-db5d-46e8-a391-d91bea186125 · outbound

This paper cites Benchmarking multi- modal llms on recognition and understanding over chemical tables.arXiv preprint arXiv:2506.11375, 2025.

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning Benchmarking multi- modal llms on recognition and understanding over chemical tables.arXiv preprint arXiv:2506.11375, 2025

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T00:22:04.590968Z

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Pith citing papers

No inbound Pith citation observations are available.