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data/2403.05034.json

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+{"paper_url": "https://huggingface.co/papers/2403.05034", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](https://huggingface.co/papers/2402.05054) (2024)\n* [CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization](https://huggingface.co/papers/2402.17214) (2024)\n* [Single-View 3D Human Digitalization with Large Reconstruction Models](https://huggingface.co/papers/2401.12175) (2024)\n* [2L3: Lifting Imperfect Generated 2D Images into Accurate 3D](https://huggingface.co/papers/2401.15841) (2024)\n* [MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction](https://huggingface.co/papers/2402.12712) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.05121.json

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+{"paper_url": "https://huggingface.co/papers/2403.05121", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion](https://huggingface.co/papers/2401.13388) (2024)\n* [UniVG: Towards UNIfied-modal Video Generation](https://huggingface.co/papers/2401.09084) (2024)\n* [ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models](https://huggingface.co/papers/2403.02084) (2024)\n* [Textual Localization: Decomposing Multi-concept Images for Subject-Driven Text-to-Image Generation](https://huggingface.co/papers/2402.09966) (2024)\n* [Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation](https://huggingface.co/papers/2402.10491) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.05135.json

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+{"paper_url": "https://huggingface.co/papers/2403.05135", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion](https://huggingface.co/papers/2401.13388) (2024)\n* [PixArt-\\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation](https://huggingface.co/papers/2403.04692) (2024)\n* [InstantID: Zero-shot Identity-Preserving Generation in Seconds](https://huggingface.co/papers/2401.07519) (2024)\n* [DiffusionGPT: LLM-Driven Text-to-Image Generation System](https://huggingface.co/papers/2401.10061) (2024)\n* [Taiyi-Diffusion-XL: Advancing Bilingual Text-to-Image Generation with Large Vision-Language Model Support](https://huggingface.co/papers/2401.14688) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.05185.json

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+{"paper_url": "https://huggingface.co/papers/2403.05185", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation](https://huggingface.co/papers/2402.02855) (2024)\n* [General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout](https://huggingface.co/papers/2402.13769) (2024)\n* [Generalized User Representations for Transfer Learning](https://huggingface.co/papers/2403.00584) (2024)\n* [Linear-Time Graph Neural Networks for Scalable Recommendations](https://huggingface.co/papers/2402.13973) (2024)\n* [Macro Graph Neural Networks for Online Billion-Scale Recommender Systems](https://huggingface.co/papers/2401.14939) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.05438.json

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+{"paper_url": "https://huggingface.co/papers/2403.05438", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Tuning-Free Noise Rectification for High Fidelity Image-to-Video Generation](https://huggingface.co/papers/2403.02827) (2024)\n* [VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models](https://huggingface.co/papers/2401.09047) (2024)\n* [AnimateLCM: Accelerating the Animation of Personalized Diffusion Models and Adapters with Decoupled Consistency Learning](https://huggingface.co/papers/2402.00769) (2024)\n* [AtomoVideo: High Fidelity Image-to-Video Generation](https://huggingface.co/papers/2403.01800) (2024)\n* [ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation](https://huggingface.co/papers/2402.04324) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.05525.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.05525", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [CoLLaVO: Crayon Large Language and Vision mOdel](https://huggingface.co/papers/2402.11248) (2024)\n* [SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models](https://huggingface.co/papers/2402.05935) (2024)\n* [InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding](https://huggingface.co/papers/2403.01487) (2024)\n* [MobileVLM V2: Faster and Stronger Baseline for Vision Language Model](https://huggingface.co/papers/2402.03766) (2024)\n* [PaLM2-VAdapter: Progressively Aligned Language Model Makes a Strong Vision-language Adapter](https://huggingface.co/papers/2402.10896) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}

data/2403.05530.json

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+{"paper_url": "https://huggingface.co/papers/2403.05530", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [World Model on Million-Length Video And Language With RingAttention](https://huggingface.co/papers/2402.08268) (2024)\n* [Repetition Improves Language Model Embeddings](https://huggingface.co/papers/2402.15449) (2024)\n* [The (R)Evolution of Multimodal Large Language Models: A Survey](https://huggingface.co/papers/2402.12451) (2024)\n* [Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT](https://huggingface.co/papers/2402.07440) (2024)\n* [Identifying Factual Inconsistency in Summaries: Towards Effective Utilization of Large Language Model](https://huggingface.co/papers/2402.12821) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}