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data/2403.09704.json

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+{"paper_url": "https://huggingface.co/papers/2403.09704", "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* [Aligners: Decoupling LLMs and Alignment](https://huggingface.co/papers/2403.04224) (2024)\n* [LAB: Large-Scale Alignment for ChatBots](https://huggingface.co/papers/2403.01081) (2024)\n* [Using Large Language Models for Natural Language Processing Tasks in Requirements Engineering: A Systematic Guideline](https://huggingface.co/papers/2402.13823) (2024)\n* [Customizing Language Model Responses with Contrastive In-Context Learning](https://huggingface.co/papers/2401.17390) (2024)\n* [SoFA: Shielded On-the-fly Alignment via Priority Rule Following](https://huggingface.co/papers/2402.17358) (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/2403.09919.json

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+{"paper_url": "https://huggingface.co/papers/2403.09919", "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* [Hydra: Sequentially-Dependent Draft Heads for Medusa Decoding](https://huggingface.co/papers/2402.05109) (2024)\n* [Speculative Streaming: Fast LLM Inference without Auxiliary Models](https://huggingface.co/papers/2402.11131) (2024)\n* [Chimera: A Lossless Decoding Method for Accelerating Large Language Models Inference by Fusing all Tokens](https://huggingface.co/papers/2402.15758) (2024)\n* [Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads](https://huggingface.co/papers/2401.10774) (2024)\n* [Ouroboros: Speculative Decoding with Large Model Enhanced Drafting](https://huggingface.co/papers/2402.13720) (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/2403.09977.json

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+{"paper_url": "https://huggingface.co/papers/2403.09977", "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* [ViT-CoMer: Vision Transformer with Convolutional Multi-scale Feature Interaction for Dense Predictions](https://huggingface.co/papers/2403.07392) (2024)\n* [MambaIR: A Simple Baseline for Image Restoration with State-Space Model](https://huggingface.co/papers/2402.15648) (2024)\n* [SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design](https://huggingface.co/papers/2401.16456) (2024)\n* [Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures](https://huggingface.co/papers/2403.02308) (2024)\n* [ELA: Efficient Local Attention for Deep Convolutional Neural Networks](https://huggingface.co/papers/2403.01123) (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/2403.09981.json

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+{"paper_url": "https://huggingface.co/papers/2403.09981", "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* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](https://huggingface.co/papers/2402.05054) (2024)\n* [Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation](https://huggingface.co/papers/2401.14257) (2024)\n* [CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization](https://huggingface.co/papers/2402.17214) (2024)\n* [SPAD : Spatially Aware Multiview Diffusers](https://huggingface.co/papers/2402.05235) (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/2403.10131.json

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+{"paper_url": "https://huggingface.co/papers/2403.10131", "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* [Unsupervised LLM Adaptation for Question Answering](https://huggingface.co/papers/2402.12170) (2024)\n* [RA-ISF: Learning to Answer and Understand from Retrieval Augmentation via Iterative Self-Feedback](https://huggingface.co/papers/2403.06840) (2024)\n* [Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge](https://huggingface.co/papers/2403.01432) (2024)\n* [Instruction-tuned Language Models are Better Knowledge Learners](https://huggingface.co/papers/2402.12847) (2024)\n* [Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately](https://huggingface.co/papers/2402.01722) (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/2403.10242.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.10242", "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* [SPAD : Spatially Aware Multiview Diffusers](https://huggingface.co/papers/2402.05235) (2024)\n* [GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting](https://huggingface.co/papers/2402.10259) (2024)\n* [Envision3D: One Image to 3D with Anchor Views Interpolation](https://huggingface.co/papers/2403.08902) (2024)\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [2L3: Lifting Imperfect Generated 2D Images into Accurate 3D](https://huggingface.co/papers/2401.15841) (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/2403.10301.json

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+{"paper_url": "https://huggingface.co/papers/2403.10301", "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* [SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis](https://huggingface.co/papers/2403.01976) (2024)\n* [Scientific Language Modeling: A Quantitative Review of Large Language Models in Molecular Science](https://huggingface.co/papers/2402.04119) (2024)\n* [ChemLLM: A Chemical Large Language Model](https://huggingface.co/papers/2402.06852) (2024)\n* [CPSDBench: A Large Language Model Evaluation Benchmark and Baseline for Chinese Public Security Domain](https://huggingface.co/papers/2402.07234) (2024)\n* [Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models](https://huggingface.co/papers/2403.00231) (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/2403.10395.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.10395", "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* [Envision3D: One Image to 3D with Anchor Views Interpolation](https://huggingface.co/papers/2403.08902) (2024)\n* [CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization](https://huggingface.co/papers/2402.17214) (2024)\n* [Make-Your-3D: Fast and Consistent Subject-Driven 3D Content Generation](https://huggingface.co/papers/2403.09625) (2024)\n* [Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation](https://huggingface.co/papers/2401.14257) (2024)\n* [SPAD : Spatially Aware Multiview Diffusers](https://huggingface.co/papers/2402.05235) (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/2403.10425.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.10425", "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* [EffLoc: Lightweight Vision Transformer for Efficient 6-DOF Camera Relocalization](https://huggingface.co/papers/2402.13537) (2024)\n* [DeFlow: Decoder of Scene Flow Network in Autonomous Driving](https://huggingface.co/papers/2401.16122) (2024)\n* [Efficient LoFTR: Semi-Dense Local Feature Matching with Sparse-Like Speed](https://huggingface.co/papers/2403.04765) (2024)\n* [A New Method for Vehicle Logo Recognition Based on Swin Transformer](https://huggingface.co/papers/2401.15458) (2024)\n* [Fast Kernel Scene Flow](https://huggingface.co/papers/2403.05896) (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/2403.10493.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.10493", "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* [SpecDiff-GAN: A Spectrally-Shaped Noise Diffusion GAN for Speech and Music Synthesis](https://huggingface.co/papers/2402.01753) (2024)\n* [EVA-GAN: Enhanced Various Audio Generation via Scalable Generative Adversarial Networks](https://huggingface.co/papers/2402.00892) (2024)\n* [ScoreDec: A Phase-preserving High-Fidelity Audio Codec with A Generalized Score-based Diffusion Post-filter](https://huggingface.co/papers/2401.12160) (2024)\n* [Ultra-lightweight Neural Differential DSP Vocoder For High Quality Speech Synthesis](https://huggingface.co/papers/2401.10460) (2024)\n* [Fast Timing-Conditioned Latent Audio Diffusion](https://huggingface.co/papers/2402.04825) (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/2403.10517.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.10517", "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* [Question-Instructed Visual Descriptions for Zero-Shot Video Question Answering](https://huggingface.co/papers/2402.10698) (2024)\n* [LLMs Meet Long Video: Advancing Long Video Comprehension with An Interactive Visual Adapter in LLMs](https://huggingface.co/papers/2402.13546) (2024)\n* [Video ReCap: Recursive Captioning of Hour-Long Videos](https://huggingface.co/papers/2402.13250) (2024)\n* [VTG-GPT: Tuning-Free Zero-Shot Video Temporal Grounding with GPT](https://huggingface.co/papers/2403.02076) (2024)\n* [LSTP: Language-guided Spatial-Temporal Prompt Learning for Long-form Video-Text Understanding](https://huggingface.co/papers/2402.16050) (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`"}