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Victor Mustar
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📢 Awesome Multimodal Modeling We introduce Awesome Multimodal Modeling, a curated repository tracing the architectural evolution of multimodal intelligence—from foundational fusion to native omni-models. 🔹 Taxonomy & Evolution: Traditional Multimodal Learning – Foundational work on representation, fusion, and alignment. Multimodal LLMs (MLLMs) – Architectures connecting vision encoders to LLMs for understanding. Unified Multimodal Models (UMMs) – Models unifying Understanding + Generation via Diffusion, Autoregressive, or Hybrid paradigms. Native Multimodal Models (NMMs) – Models trained from scratch on all modalities; contrasts early vs. late fusion under scaling laws. 💡 Key Distinction: UMMs unify tasks via generation heads; NMMs enforce interleaving through joint pre-training. 🔗 Explore & Contribute: https://github.com/OpenEnvision-Lab/Awesome-Multimodal-Modeling
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victor
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victor/claude-code-sessions
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victor/llama-agent-sessions
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victor/context-1-corpus
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victor/autotrain-gemma-json-data
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victor/claude-sample-session
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victor/codex-sample-session
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victor/pi-sample-session
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victor/opencode-sample-session
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victor/coding-agent-sessions
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victor/temp-hardware-images
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victor/nanbeige4.1-3b-vs-gpt4o-wildbench
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victor/nanbeige4.1-3b-vs-gpt4o-wildchat
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victor/acestep-outputs
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victor/acestep-job-script
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victor/functiongemma-agent-sft
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victor/GraspClutter6D
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victor/InfLLM-V2-data-5B
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victor/LMSYS-Chat-GPT-5-Chat-Response
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victor/ToolScale
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victor/test22222
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victor/aime_2023_I-logs
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victor/glm-4.6-exercism-logs
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victor/my_first_lora_v1-dataset222222
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victor/my_first_lora_v1-dataset22
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victor/aze
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victor/my_first_lora_v1-dataset
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victor/test
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victor/obj
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victor/mutti-product-pictures
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victor/random-images
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