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Paper Citation Record · LEDGER

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.18789.

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

pith.paper-citation-record.v1
2607.18789 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:24:46.123867Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation 693973c7-37fe-447c-abe1-2a7cd9eabb6e · outbound

This paper cites VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

Reference 3

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Unavailable: canonical work link unavailable.

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Observation 0d35a70b-b969-4c19-8217-0940589ede0c · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 5

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Observation 8a13afa6-1a26-45c5-acc6-b8c4bcb271d9 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Imagen Video: High Definition Video Generation with Diffusion Models

Reference 7

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source=pdf_text observed=2026-08-01T14:24:46.080717Z digest=sha256:249bce17e7f7d5b84878f40edf1e66fc50cfe5f6dbc07dc50b7da72295112d1f

Observation 413adb3b-7dc5-4ed3-b8d5-8b34deb0ba8c · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Latte: Latent Diffusion Transformer for Video Generation

Reference 11

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source=pdf_text observed=2026-08-01T14:24:46.092789Z digest=sha256:7ca36f627a1c153f18d353360949f78ae8fa361bad62ea841959316e3c8f35fe

Observation c9b6c558-2227-4405-a9c4-9c87dd2f600e · outbound

This paper cites Scaling Data-Constrained Language Models.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Scaling Data-Constrained Language Models

Reference 12

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source=pdf_text observed=2026-08-01T14:24:46.095609Z digest=sha256:2bfc74440a7d0c0ecf6a88acf1a19a99a68736142fda118e30e2a523a7bd11a3

Observation 58b82d0c-4db1-4c0e-a33d-613e99a7c9d2 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Movie Gen: A Cast of Media Foundation Models

Reference 13

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source=pdf_text observed=2026-08-01T14:24:46.098413Z digest=sha256:de4b632ac22267681ecd3fa6fd81cffc9afcdc6b2fbbf22f2692931538daddd4

Observation ae690f68-872e-40e2-b250-fb8819585b03 · outbound

This paper cites The layout bet, June 2026.https://reve.com.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation The layout bet, June 2026.https://reve.com

Reference 14

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source=pdf_text observed=2026-08-01T14:24:46.101322Z digest=sha256:352ba4937f6142ff5b1b9406fec039baea3823e26184d52870aabf9ba70fd073

Observation dc336a12-9133-4c2f-ac8d-cf08f5064aef · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 15

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source=pdf_text observed=2026-08-01T14:24:46.104418Z digest=sha256:00de47ff94a7fe493a5b70c056ee6ab11407f0d50b02440503de7bdbfde398db

Observation 2d70f25d-88dd-472f-a9bd-ff865892816d · outbound

This paper cites Kimi-VL Technical Report.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Kimi-VL Technical Report

Reference 16

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source=pdf_text observed=2026-08-01T14:24:46.107195Z digest=sha256:8ded24a321ad2c97fd0b2de7a4e623c41114c360617b3b3389174dfb3037ac69

Observation 2c439224-b816-4c81-a181-933ffe2909de · outbound

This paper cites InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Reference 17

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source=pdf_text observed=2026-08-01T14:24:46.109969Z digest=sha256:3f145074d4c0409fbde628059b27a05de6333cec51a49557fd2977917b4356f1

Observation 74041b2e-5c19-4a61-af00-d706787a76e5 · outbound

This paper cites Qwen3 Technical Report.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Qwen3 Technical Report

Reference 18

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source=pdf_text observed=2026-08-01T14:24:46.112606Z digest=sha256:4a92986d9b5cf69642714039bc9fc6bd647d71dc04b72d16c1d6701a5ed86eae

Observation 769ef145-26bf-4f10-98fb-44334ddf91d5 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 19

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source=pdf_text observed=2026-08-01T14:24:46.115337Z digest=sha256:dc029d0849e8df4514f081d4c5e5ab5a0fea64d5b90fc79646805365b0e138b2

Observation 22de8f3c-08d4-4808-a226-b81939f715aa · outbound

This paper cites Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance

Reference 20

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source=pdf_text observed=2026-08-01T14:24:46.118299Z digest=sha256:e6439cfc8811e160ea1da36a703c3c5471d53896f19407e3239a1b2fe197e417

Observation b3bf8dc0-9717-4763-8671-a51cf65f0121 · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Open-Sora: Democratizing Efficient Video Production for All

Reference 21

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source=pdf_text observed=2026-08-01T14:24:46.121154Z digest=sha256:c8342cde323bf5639a0c968f98834d5bcbc34f83e053eb6546832e15671664ce

Observation 3d381a34-1eec-44a7-ba60-4cb63def9d77 · outbound

This paper cites 4 lists all attributes used in the Moving Alphabet dataset and their possible values.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation 4 lists all attributes used in the Moving Alphabet dataset and their possible values

Reference 22

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source=pdf_text observed=2026-08-01T14:24:46.123867Z digest=sha256:300f4198d3d7d746ab818724281cccfb5f26d406172bc11454b327564d248952

Observation b2c9eb7a-83df-48e9-b52f-0adfc932bb45 · outbound

This paper cites Scaling Laws for Neural Language Models.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Scaling Laws for Neural Language Models

Reference 2017

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source=pdf_text observed=2026-08-01T14:24:46.086843Z digest=sha256:aa923db7a81877b22a3f214ce136b6607b8c9e97c38368744c1264b3ab0a6e50

Observation b6b3cb75-426b-4279-ab51-ca0b52e2215d · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 2018

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source=pdf_text observed=2026-08-01T14:24:46.089947Z digest=sha256:08b086eb26cf39b33f58c50498d081c8c9a00bfc89e41216bf7cd469d67a0b83

Observation ccea6b25-c376-4495-8069-b4f379bc0dea · outbound

This paper cites Classifier-Free Diffusion Guidance.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Classifier-Free Diffusion Guidance

Reference 2020

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source=pdf_text observed=2026-08-01T14:24:46.077417Z digest=sha256:6a0e9e554c38e4649d95de755274ec2a45bc58030feb08be3c7b9dac3c6a4e2d

Observation 73280caa-25ab-44dd-b35d-df6f459a6509 · outbound

This paper cites T2I-CompBench++: An Enhanced and Comprehensive Benchmark for Compositional Text-to-image Generation.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation T2I-CompBench++: An Enhanced and Comprehensive Benchmark for Compositional Text-to-image Generation

Reference 2022

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source=pdf_text observed=2026-08-01T14:24:46.083996Z digest=sha256:fdf2e5b35c0de3cf78af1df818b833bc12a0901adf647a04ee4f14444497e381

Observation fecae1f6-d53c-4734-abb8-b07da78f8706 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2023

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source=pdf_text observed=2026-08-01T14:24:46.064539Z digest=sha256:004348a25a883421fa99f8dc0bdd722c3164e78751bc724cafd4514389ad321e

Observation 1607a6e6-7344-473d-bc6e-1917f964994a · outbound

This paper cites Lumiere: A Space-Time Diffusion Model for Video Generation.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation Lumiere: A Space-Time Diffusion Model for Video Generation

Reference 2024

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source=pdf_text observed=2026-08-01T14:24:46.060545Z digest=sha256:1cd29491e1ed9ca9031d140219c0d460b7102fa323423b0a2bf047bb6c383a61

Observation f06cfb1f-d129-48dc-bc79-00a4a6f15663 · outbound

This paper cites TinyStories: How Small Can Language Models Be and Still Speak Coherent English?.

Moving Alphabet: A Controlled Study of Training Data for Text-to-Video Generation TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.