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Paper Citation Record · LEDGER

Question Answering for Diagram-Rich Technical Meeting Videos

As of 7 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2607.10494.

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

pith.paper-citation-record.v1
2607.10494 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T11:18:03.535674Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

40 of 40 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved39
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a8ab4a2-e731-47df-b90e-54cb496faa4c · outbound

This paper cites Requirements engineering in the year 00: A re- search perspective,.

Question Answering for Diagram-Rich Technical Meeting Videos Requirements engineering in the year 00: A re- search perspective,

Reference 1

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Observation 5f8f91bd-c0c8-4080-9329-930c1b7d9868 · outbound

This paper cites Effectiveness of elicitation techniques in distributed requirements engineering,.

Question Answering for Diagram-Rich Technical Meeting Videos Effectiveness of elicitation techniques in distributed requirements engineering,

Reference 2

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Observation f0719824-b31e-4a15-acce-38a3271a010a · outbound

This paper cites Hy- perMeeting: Supporting asynchronous meetings with hypervideo,.

Question Answering for Diagram-Rich Technical Meeting Videos Hy- perMeeting: Supporting asynchronous meetings with hypervideo,

Reference 3

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:27d6870c608adf2df0ff5f58a6c51ea0903f89704f49dfc61a3121565408d18a

Observation 28b0f599-a679-48b7-bdd9-f31ce9995041 · outbound

This paper cites Turning asyn- chronicity into an opportunity: asynchronous communication for shared understanding with vision videos,.

Question Answering for Diagram-Rich Technical Meeting Videos Turning asyn- chronicity into an opportunity: asynchronous communication for shared understanding with vision videos,

Reference 4

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Observation b0faeb59-163f-4525-8c89-36752d919462 · outbound

This paper cites A comparison of asynchronous online text-based lectures and synchronous interactive web conferencing lectures,.

Question Answering for Diagram-Rich Technical Meeting Videos A comparison of asynchronous online text-based lectures and synchronous interactive web conferencing lectures,

Reference 5

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:04e30dff77f444614d3d5a85b0fc159fc6ab26ac19b8771bee7d75d99d39be51

Observation 9a2ccbe7-f962-4618-95d8-acd86d9e9198 · outbound

This paper cites Team-based learning in asynchronous online settings,.

Question Answering for Diagram-Rich Technical Meeting Videos Team-based learning in asynchronous online settings,

Reference 6

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:44f64b5a97ee9984e4234a7c3b033b3c70c8df05796ff7d208fbf92243c868c1

Observation a7cdb65f-7d1b-4fbb-a39a-d86b685a453e · outbound

This paper cites CodeTube: Extracting relevant fragments from software development video tutorials,.

Question Answering for Diagram-Rich Technical Meeting Videos CodeTube: Extracting relevant fragments from software development video tutorials,

Reference 7

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Observation 41cdd7c6-394e-440f-8853-1ca3cc144874 · outbound

This paper cites Text retrieval-based tagging of software engineering video tutorials,.

Question Answering for Diagram-Rich Technical Meeting Videos Text retrieval-based tagging of software engineering video tutorials,

Reference 8

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:b8689a07707bf90530cb248c0fb854a03c664314fca3887980a34ab8c18d51eb

Observation 5f1fb1ee-f18a-4b6e-bfef-3eefd17ecd02 · outbound

This paper cites Automatic tag recommen- dation for software development video tutorials,.

Question Answering for Diagram-Rich Technical Meeting Videos Automatic tag recommen- dation for software development video tutorials,

Reference 9

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Observation 1ff50a4a-4eca-4f4e-ac4f-4f660a2f2a97 · outbound

This paper cites psc2code: Denois- ing code extraction from programming screencasts,.

Question Answering for Diagram-Rich Technical Meeting Videos psc2code: Denois- ing code extraction from programming screencasts,

Reference 10

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Observation f82d7c36-5df4-46d3-8176-14fa15dad1dc · outbound

This paper cites VT-Revolution: Interactive programming video tutorial authoring and watching system,.

Question Answering for Diagram-Rich Technical Meeting Videos VT-Revolution: Interactive programming video tutorial authoring and watching system,

Reference 11

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Observation 6ab463b6-2180-43c2-9c7b-a5283520ef5b · outbound

This paper cites Improving code extraction from coding screencasts using a code-aware encoder-decoder model,.

Question Answering for Diagram-Rich Technical Meeting Videos Improving code extraction from coding screencasts using a code-aware encoder-decoder model,

Reference 12

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Observation 316f4ffe-43cd-4849-a4f5-30f1846e3dbe · outbound

This paper cites Efficient search of live-coding screen- casts from online videos,.

Question Answering for Diagram-Rich Technical Meeting Videos Efficient search of live-coding screen- casts from online videos,

Reference 13

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Observation 61b73085-4dfb-4887-9bbf-ca17af374fec · outbound

This paper cites Semantic GUI scene learning and video alignment for detecting du- plicate video-based bug reports,.

Question Answering for Diagram-Rich Technical Meeting Videos Semantic GUI scene learning and video alignment for detecting du- plicate video-based bug reports,

Reference 14

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Observation 00ff2e3a-5eab-42c1-b8e6-831cf12401d9 · outbound

This paper cites Question answering for multi-release systems: A case study at ciena,.

Question Answering for Diagram-Rich Technical Meeting Videos Question answering for multi-release systems: A case study at ciena,

Reference 15

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Observation 4566be2e-7321-4248-be72-f5c9a2f06a57 · outbound

This paper cites Developing a llama-based chatbot for CI/CD question answer- ing: A case study at ericsson,.

Question Answering for Diagram-Rich Technical Meeting Videos Developing a llama-based chatbot for CI/CD question answer- ing: A case study at ericsson,

Reference 16

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:f7e82ebce522eb96960618ca7e126f98bf9f2528e8e45775556c79078d5b7b5d

Observation ae4d2485-96f7-4453-81b9-32689cfb1d6f · outbound

This paper cites Experiences developing an AI chatbot in the pharmaceutical industry,.

Question Answering for Diagram-Rich Technical Meeting Videos Experiences developing an AI chatbot in the pharmaceutical industry,

Reference 17

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Observation 985e0d00-3c15-4ca6-9e84-b6b50f1eecbb · outbound

This paper cites Evaluating large language models for requirements question answering in industrial aerospace software,.

Question Answering for Diagram-Rich Technical Meeting Videos Evaluating large language models for requirements question answering in industrial aerospace software,

Reference 18

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Observation c37f6bc6-5dc8-4f97-908e-d03970107a58 · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

Question Answering for Diagram-Rich Technical Meeting Videos Flamingo: a Visual Language Model for Few-Shot Learning

Reference 19

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Observation 7411e653-c222-47b0-a647-dee8e509545f · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

Question Answering for Diagram-Rich Technical Meeting Videos Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 20

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Observation da5b67d3-f8aa-4364-80f4-51a8edb1614b · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

Question Answering for Diagram-Rich Technical Meeting Videos Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 21

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Observation 4653a386-0d96-45eb-9710-ca91719658ed · outbound

This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

Question Answering for Diagram-Rich Technical Meeting Videos Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 22

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:4a6eb7a199877aebd6eb13ec949fb8fbe4eae1b797a11465ca5ebd335383c869

Observation e8b7154d-d853-4d53-9750-9072cc73c1ea · outbound

This paper cites DrVideo: Document retrieval based long video understanding,.

Question Answering for Diagram-Rich Technical Meeting Videos DrVideo: Document retrieval based long video understanding,

Reference 23

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:4ea03d6dbd265b48a28c363db177c8ce2d432a21de07bc833e10ab1ab67110d7

Observation 7795e9dc-b4dd-44c0-8e8f-4b22a3eec4d0 · outbound

This paper cites A simple LLM framework for long-range video question- answering,.

Question Answering for Diagram-Rich Technical Meeting Videos A simple LLM framework for long-range video question- answering,

Reference 24

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:b7778baa435f3289ff8de57e5d5919d6288f61c9d015b3dd9bf4127926c0e4f9

Observation 51b8ce65-072e-45b5-80fa-82884c1c442e · outbound

This paper cites LongVLM: Efficient Long Video Understanding via Large Language Models.

Question Answering for Diagram-Rich Technical Meeting Videos LongVLM: Efficient Long Video Understanding via Large Language Models

Reference 25

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Observation 4da5208d-d192-44f1-9397-632441809cd9 · outbound

This paper cites LMVQA: Prompts, resources, codes, and interviews for the LMVQA system,.

Question Answering for Diagram-Rich Technical Meeting Videos LMVQA: Prompts, resources, codes, and interviews for the LMVQA system,

Reference 26

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Observation d8f8c2a2-b2fe-401d-b809-5ba8526daf98 · outbound

This paper cites Frame rates explained: Why FPS matters in broadcasting,.

Question Answering for Diagram-Rich Technical Meeting Videos Frame rates explained: Why FPS matters in broadcasting,

Reference 27

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Observation 94c416d5-1c0d-4809-8a02-b5165cb3b679 · outbound

This paper cites Image quality assessment: From error visibility to structural similarity,.

Question Answering for Diagram-Rich Technical Meeting Videos Image quality assessment: From error visibility to structural similarity,

Reference 28

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Observation f5759fef-7f49-4806-bb2c-f4327b4a8acc · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Question Answering for Diagram-Rich Technical Meeting Videos Chain-of-thought prompting elicits reasoning in large language models,

Reference 29

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:4c25f750abdb56aa97bb56e0e6e928dba30ad5c083c42ac8616d005783a47108

Observation d7ea6fc4-e6b4-4763-a36b-a4557003818b · outbound

This paper cites Language models are few-shot learners,.

Question Answering for Diagram-Rich Technical Meeting Videos Language models are few-shot learners,

Reference 30

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Observation 6c3e4a53-fc1b-4854-8d30-545962f1e2d5 · outbound

This paper cites Robust speech recognition via large-scale weak supervi- sion,.

Question Answering for Diagram-Rich Technical Meeting Videos Robust speech recognition via large-scale weak supervi- sion,

Reference 31

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Observation 332e1848-e64a-41fc-8f79-5005d589733e · outbound

This paper cites A vector space model for automatic indexing,.

Question Answering for Diagram-Rich Technical Meeting Videos A vector space model for automatic indexing,

Reference 32

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Observation d902558f-71b3-41ac-a61e-01c07847b527 · outbound

This paper cites The measurement of observer agreement for categorical data,.

Question Answering for Diagram-Rich Technical Meeting Videos The measurement of observer agreement for categorical data,

Reference 33

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Observation 61e9759e-486a-4f14-b756-c277fc6745e4 · outbound

This paper cites PlotQA: Reasoning over scientific plots,.

Question Answering for Diagram-Rich Technical Meeting Videos PlotQA: Reasoning over scientific plots,

Reference 34

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Observation b0b46faf-e64a-49c6-ba2c-2b02fa9bc7aa · outbound

This paper cites ChartQA: A benchmark for question answering about charts with visual and logical reasoning,.

Question Answering for Diagram-Rich Technical Meeting Videos ChartQA: A benchmark for question answering about charts with visual and logical reasoning,

Reference 35

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Observation 82db81db-d768-4f53-a087-ca3ca07f51ab · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

Question Answering for Diagram-Rich Technical Meeting Videos ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 36

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Observation fb1cabaa-f089-414d-a89a-d5c6c26e1447 · outbound

This paper cites A diagram is worth a dozen images,.

Question Answering for Diagram-Rich Technical Meeting Videos A diagram is worth a dozen images,

Reference 37

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Observation 3a267bd8-37b8-423d-b29b-afdb86527899 · outbound

This paper cites DocVQA: A dataset for VQA on document images,.

Question Answering for Diagram-Rich Technical Meeting Videos DocVQA: A dataset for VQA on document images,

Reference 38

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source=pdf_text observed=2026-07-14T11:18:03.535674Z digest=sha256:4f29b2831cbd5c385ff1af4b76c72abc8927a2a4827215b4a3d1e668f8594bc2

Observation df79178a-08ea-4ad0-a925-dd872eefaacc · outbound

This paper cites Test input validation for vision-based dl systems: An active learning approach,.

Question Answering for Diagram-Rich Technical Meeting Videos Test input validation for vision-based dl systems: An active learning approach,

Reference 39

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malformed identifier
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Observation 83d9cffe-3868-4736-b318-b167dc87a27b · outbound

This paper cites Milvus: A purpose-built vector data management system,.

Question Answering for Diagram-Rich Technical Meeting Videos Milvus: A purpose-built vector data management system,

Reference 40

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