ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement | Paper Citation Record

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This paper cites Frozen in time: A joint video and image encoder for end-to-end retrieval.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Frozen in time: A joint video and image encoder for end-to-end retrieval

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This paper cites Lumiere: A space-time dif- fusion model for video generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Lumiere: A space-time dif- fusion model for video generation

Reference 2

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This paper cites Improving image generation with better captions.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Improving image generation with better captions

Reference 3

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This paper cites Align your latents: High-resolution video synthesis with la- tent diffusion models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 4

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This paper cites In- structpix2pix: Learning to follow image editing instructions.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement In- structpix2pix: Learning to follow image editing instructions

Reference 5

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This paper cites Video generation models as world simulators.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Video generation models as world simulators

Reference 6

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This paper cites VideoCrafter1: Open Diffusion Models for High-Quality Video Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 7

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This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffu- sion models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Videocrafter2: Overcoming data limitations for high-quality video diffu- sion models

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This paper cites Pixart-alpha: Fast training of diffusion transformer for photorealistic text-to-image syn- thesis.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Pixart-alpha: Fast training of diffusion transformer for photorealistic text-to-image syn- thesis

Reference 9

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This paper cites Panda-70m: Captioning 70m videos with multiple cross-modality teachers.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Panda-70m: Captioning 70m videos with multiple cross-modality teachers

Reference 10

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Observation 1857c1e7-f202-4dc7-b3bc-572ceb3da728 · outbound

This paper cites Contin- ual pre-training mitigates forgetting in language and vision.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Contin- ual pre-training mitigates forgetting in language and vision

Reference 11

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This paper cites A continual learning survey: Defying for- getting in classification tasks.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement A continual learning survey: Defying for- getting in classification tasks

Reference 12

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This paper cites Irc- gan: Introspective recurrent convolutional gan for text-to- video generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Irc- gan: Introspective recurrent convolutional gan for text-to- video generation

Reference 13

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This paper cites Catastrophic forgetting in connectionist networks.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Catastrophic forgetting in connectionist networks

Reference 14

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This paper cites Videostu- dio: Generating consistent-content and multi-scene videos.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Videostu- dio: Generating consistent-content and multi-scene videos

Reference 15

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This paper cites Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers

Reference 16

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This paper cites Preserve your own correlation: A noise prior for video diffusion models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Preserve your own correlation: A noise prior for video diffusion models

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This paper cites SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 18

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This paper cites Animatediff: Animate your personalized text-to- image diffusion models without specific tuning.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Animatediff: Animate your personalized text-to- image diffusion models without specific tuning

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Observation e2eb497d-0d51-4551-bac0-1f4449f9b56d · outbound

This paper cites Photorealistic video generation with diffusion models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Photorealistic video generation with diffusion models

Reference 20

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This paper cites Latent Video Diffusion Models for High-Fidelity Long Video Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Latent Video Diffusion Models for High-Fidelity Long Video Generation

Reference 21

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This paper cites Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation

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This paper cites LLMs Meet Multimodal Generation and Editing: A Survey.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement LLMs Meet Multimodal Generation and Editing: A Survey

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

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Imagen Video: High Definition Video Generation with Diffusion Models

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Video dif- fusion models

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This paper cites DirecT2V: Large Language Models are Frame-Level Directors for Zero-Shot Text-to-Video Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement DirecT2V: Large Language Models are Frame-Level Directors for Zero-Shot Text-to-Video Generation

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This paper cites Parameter-efficient transfer learning for nlp.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Parameter-efficient transfer learning for nlp

Reference 27

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This paper cites Lora: Low- rank adaptation of large language models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Lora: Low- rank adaptation of large language models

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This paper cites VBench: Com- prehensive benchmark suite for video generative models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement VBench: Com- prehensive benchmark suite for video generative models

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Simple and Scalable Strategies to Continually Pre-train Large Language Models

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Continual pre-training of language models

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Open-sora-plan, 2024

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This paper cites Llava-next: Tack- ling multi-image, video, and 3d in large multimodal models,.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Llava-next: Tack- ling multi-image, video, and 3d in large multimodal models,

Reference 33

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Video generation from text

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Llm-grounded video diffusion models

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Latte: Latent Diffusion Transformer for Video Generation

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Snap video: Scaled spatiotemporal transformers for text-to-video synthesis

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Sync-draw: Automatic video generation using deep recurrent attentive architectures

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This paper cites Jour- neydb: A benchmark for generative image understanding,.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Jour- neydb: A benchmark for generative image understanding,

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Scalable diffusion models with transformers

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This paper cites Learning transferable visual models from natural language supervi- sion.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Learning transferable visual models from natural language supervi- sion

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This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Exploring the limits of transfer learning with a unified text-to-text transformer

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This paper cites T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation

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This paper cites Emu: Generative Pretraining in Multimodality.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Emu: Generative Pretraining in Multimodality

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Generative multimodal mod- els are in-context learners

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Neural discrete representation learning

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This paper cites Magicvideo-v2: Multi-stage high-aesthetic video generation, 2024.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Magicvideo-v2: Multi-stage high-aesthetic video generation, 2024

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This paper cites TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models

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This paper cites Emu3: Next-Token Prediction is All You Need.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Emu3: Next-Token Prediction is All You Need

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This paper cites LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

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ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement LLaMA pro: Progressive LLaMA with block expansion

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This paper cites Vript: A video is worth thousands of words, 2024.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Vript: A video is worth thousands of words, 2024

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Observation c755604e-2b24-4701-8e21-fe7597d3bb59 · outbound

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

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

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Observation 5cc165ec-c1aa-4c8b-8db4-733edfaaf277 · outbound

This paper cites Language model beats diffusion-tokenizer is key to visual generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Language model beats diffusion-tokenizer is key to visual generation

Reference 54

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Observation 8f96385c-1f72-4902-8aac-1f7e543c5e7c · outbound

This paper cites Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation

Reference 55

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Observation cb8924cb-da26-4933-a0ca-c805c9a3a61e · outbound

This paper cites Open-sora: Democratizing efficient video production for all, 2024.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement Open-sora: Democratizing efficient video production for all, 2024

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T01:04:36.218328Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e05f910e-1c09-4a7a-834a-311f74a36604 · outbound

This paper cites MagicVideo: Efficient Video Generation With Latent Diffusion Models.

ModelGrow: Continual Text-to-Video Pre-training with Model Expansion and Language Understanding Enhancement MagicVideo: Efficient Video Generation With Latent Diffusion Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T01:04:35.416676Z

Source-reported events for the cited work

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