Paper Citation Record · LEDGER

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models

As of 18 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2501.09672.

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

pith.paper-citation-record.v1
2501.09672 v3

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:51:25.887796Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 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

36 of 36 outbound references displayed

verified exact0
verified fuzzy20
unresolved16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8c55e834-d644-4453-8609-4029da6d3356 · outbound

This paper cites write newline.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models write newline

Reference 1

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Source-reported events for the cited work

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Observation e5e8a8d6-36d6-4fbd-932d-ce30f36737e1 · outbound

This paper cites Scaling laws for generative mixed-modal language models.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Scaling laws for generative mixed-modal language models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:25.609109Z

Source-reported events for the cited work

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Observation 965ccf86-cf63-490a-897b-12180214a7c0 · outbound

This paper cites Lawrence Zitnick, Dhruv Batra, and Devi Parikh.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Lawrence Zitnick, Dhruv Batra, and Devi Parikh

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:27.092949Z

Source-reported events for the cited work

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Observation 6d0c078c-27ad-407d-a6ed-4e6ece8b1d9c · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Pythia: A suite for analyzing large language models across training and scaling

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:27.070866Z

Source-reported events for the cited work

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Observation c1e84e37-393c-4d22-8f32-ba5994008391 · outbound

This paper cites PaLI: A Jointly-Scaled Multilingual Language-Image Model.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models PaLI: A Jointly-Scaled Multilingual Language-Image Model

Reference 5

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Source-reported events for the cited work

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Observation 4a69c8f5-4d07-41d0-a6df-3c0be1f202f7 · outbound

This paper cites Reproducible scaling laws for contrastive language-image learning.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Reproducible scaling laws for contrastive language-image learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:27.024753Z

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Observation 071960fb-a29d-496e-8816-80874bbf38f9 · outbound

This paper cites A coefficient of agreement for nominal scales.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models A coefficient of agreement for nominal scales

Reference 7

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Source-reported events for the cited work

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Observation 988c5c71-494e-4961-830f-8d3f9587a9b7 · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answering.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Making the v in vqa matter: Elevating the role of image understanding in visual question answering

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.985702Z

Source-reported events for the cited work

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Observation c6eb6c26-6232-4cd0-9d38-a5c1ee17599a · outbound

This paper cites Sugarcrepe: Fixing hackable benchmarks for vision-language compositionality.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Sugarcrepe: Fixing hackable benchmarks for vision-language compositionality

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.963085Z

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Observation 6c988c71-d243-4fc3-9eef-0e37e0e2f402 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.924608Z

Source-reported events for the cited work

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Observation 774765d2-7178-4461-83e5-b0083ccf2e89 · outbound

This paper cites Hudson and Christopher D.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Hudson and Christopher D

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.884643Z

Source-reported events for the cited work

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Observation 8db6cee1-d9a2-4de2-87ea-42797afbda03 · outbound

This paper cites Scaling laws for downstream task performance of large language models.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Scaling laws for downstream task performance of large language models

Reference 12

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Source-reported events for the cited work

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Observation 3b5fe3cc-cb98-4dd6-aad3-c45194caa9b6 · outbound

This paper cites Large Language Models as Automated Aligners for benchmarking Vision-Language Models.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Large Language Models as Automated Aligners for benchmarking Vision-Language Models

Reference 13

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Source-reported events for the cited work

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Observation 8ef415a1-fb34-4b4f-abe4-43da84becfff · outbound

This paper cites Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.857063Z

Source-reported events for the cited work

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Observation 6b7b52ec-d510-4b2a-ae3e-41f8d6522a8a · outbound

This paper cites Benchmarking Cognitive Biases in Large Language Models as Evaluators.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 15

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Source-reported events for the cited work

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Observation e27249bc-83bf-4033-be89-10cf8fb087ee · outbound

This paper cites Shamma, Michael S.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Shamma, Michael S

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.835213Z

Source-reported events for the cited work

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Observation 467e27ca-f6fd-446c-abb4-d96ef405a73f · outbound

This paper cites Richard Landis and Gary G.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Richard Landis and Gary G

Reference 17

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Source-reported events for the cited work

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Observation 295d2df2-2f49-4ca0-9b70-0c7fd212d330 · outbound

This paper cites Prometheus-Vision: Vision-Language Model as a Judge for Fine-Grained Evaluation.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Prometheus-Vision: Vision-Language Model as a Judge for Fine-Grained Evaluation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:25.740068Z

Source-reported events for the cited work

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Observation 832ef200-8aa7-41d0-b0c2-4e95a6ee8bcc · outbound

This paper cites Hashimoto.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Hashimoto

Reference 19

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Source-reported events for the cited work

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Observation 42bc1c55-1abe-433d-827b-4849628fe22f · outbound

This paper cites Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models

Reference 20

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Source-reported events for the cited work

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Observation f93b1673-c777-4a6a-804c-9f1346b0fbe6 · outbound

This paper cites Lawrence Zitnick, and Piotr Dollár.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Lawrence Zitnick, and Piotr Dollár

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.785676Z

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Observation f734faa6-9cdb-458f-896e-ed141fc023fb · outbound

This paper cites Improved Baselines with Visual Instruction Tuning , 2023 a.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Improved Baselines with Visual Instruction Tuning , 2023 a

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.768831Z

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Observation 2334d8b9-6bf9-41b2-a240-d44b5099203c · outbound

This paper cites Visual Instruction Tuning , 2023 b.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Visual Instruction Tuning , 2023 b

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.743919Z

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Observation 02fdbc1d-1582-4b13-afc6-ae23afd06637 · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.724928Z

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Observation ea1380d3-e1ef-4445-b172-78babf8c9908 · outbound

This paper cites OCR-VQA: Visual Question Answering by Reading Text in Images.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models OCR-VQA: Visual Question Answering by Reading Text in Images

Reference 25

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Observation ee15cd68-f4a2-422f-953d-733d0c764825 · outbound

This paper cites Gpt-4v(ision) system card.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Gpt-4v(ision) system card

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.699551Z

Source-reported events for the cited work

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Observation 4899d78b-0e84-4e0c-bf73-8b28a0560d7b · outbound

This paper cites Openai model documentation.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Openai model documentation

Reference 27

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Source-reported events for the cited work

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Observation 85cee05d-d53c-48d8-804c-823981f7e093 · outbound

This paper cites Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever

Reference 28

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Source-reported events for the cited work

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Observation 5520d006-a753-4346-baf9-c42044b301bb · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Direct preference optimization: Your language model is secretly a reward model

Reference 29

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Observation a6f9c3a3-9ba9-439d-9ba8-d1b2ac43344c · outbound

This paper cites Revisiting the train loss: an efficient performance estimator for neural architecture search, 06 2020.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Revisiting the train loss: an efficient performance estimator for neural architecture search, 06 2020

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.595617Z

Source-reported events for the cited work

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Observation 2671ea9d-312b-46c0-9bf5-8dc13fd2d1c5 · outbound

This paper cites Towards vqa models that can read.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Towards vqa models that can read

Reference 31

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Source-reported events for the cited work

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Observation 20c47a55-3e47-4ebe-9ece-ddbf32f870df · outbound

This paper cites Generative Multimodal Models are In-Context Learners.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Generative Multimodal Models are In-Context Learners

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:25.852957Z

Source-reported events for the cited work

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Observation 85d87149-19c4-45c4-bece-1d2d06fd2cbb · outbound

This paper cites Székely, Maria L.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Székely, Maria L

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:25.866465Z

Source-reported events for the cited work

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Observation 454a078a-a3e9-4704-9f36-cc8df588f1eb · outbound

This paper cites Style Over Substance: Evaluation Biases for Large Language Models.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Style Over Substance: Evaluation Biases for Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T19:51:25.872740Z

Source-reported events for the cited work

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Observation 223c606b-c254-4773-86a6-2f50624c24d7 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities , 2023.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities , 2023

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.542116Z

Source-reported events for the cited work

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Observation 7f77c188-126e-456f-9203-a7c136f166a3 · outbound

This paper cites Xing, Hao Zhang, Joseph E.

CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models Xing, Hao Zhang, Joseph E

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:51:26.500908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.