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data/2404.18212.json

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+{"paper_url": "https://huggingface.co/papers/2404.18212", "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* [InstructGIE: Towards Generalizable Image Editing](https://huggingface.co/papers/2403.05018) (2024)\n* [StyleBooth: Image Style Editing with Multimodal Instruction](https://huggingface.co/papers/2404.12154) (2024)\n* [Locate, Assign, Refine: Taming Customized Image Inpainting with Text-Subject Guidance](https://huggingface.co/papers/2403.19534) (2024)\n* [ByteEdit: Boost, Comply and Accelerate Generative Image Editing](https://huggingface.co/papers/2404.04860) (2024)\n* [BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion](https://huggingface.co/papers/2403.06976) (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/2405.00029.json

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+{"paper_url": "https://huggingface.co/papers/2405.00029", "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* [Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification](https://huggingface.co/papers/2404.17753) (2024)\n* [The Solution for the CVPR 2023 1st foundation model challenge-Track2](https://huggingface.co/papers/2403.17702) (2024)\n* [End-to-end multi-modal product matching in fashion e-commerce](https://huggingface.co/papers/2403.11593) (2024)\n* [Multi-modal Semantic Understanding with Contrastive Cross-modal Feature Alignment](https://huggingface.co/papers/2403.06355) (2024)\n* [MeaCap: Memory-Augmented Zero-shot Image Captioning](https://huggingface.co/papers/2403.03715) (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/2405.00233.json

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+{"paper_url": "https://huggingface.co/papers/2405.00233", "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* [ESC: Efficient Speech Coding with Cross-Scale Residual Vector Quantized Transformers](https://huggingface.co/papers/2404.19441) (2024)\n* [CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech](https://huggingface.co/papers/2404.02781) (2024)\n* [PromptCodec: High-Fidelity Neural Speech Codec using Disentangled Representation Learning based Adaptive Feature-aware Prompt Encoders](https://huggingface.co/papers/2404.02702) (2024)\n* [NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models](https://huggingface.co/papers/2403.03100) (2024)\n* [Gull: A Generative Multifunctional Audio Codec](https://huggingface.co/papers/2404.04947) (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/2405.00236.json

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+{"paper_url": "https://huggingface.co/papers/2405.00236", "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* [Exploring Learning-based Motion Models in Multi-Object Tracking](https://huggingface.co/papers/2403.10826) (2024)\n* [Multiple Object Tracking as ID Prediction](https://huggingface.co/papers/2403.16848) (2024)\n* [Ego-Motion Aware Target Prediction Module for Robust Multi-Object Tracking](https://huggingface.co/papers/2404.03110) (2024)\n* [Learning Data Association for Multi-Object Tracking using Only Coordinates](https://huggingface.co/papers/2403.08018) (2024)\n* [DeconfuseTrack: Dealing with Confusion for Multi-Object Tracking](https://huggingface.co/papers/2403.02767) (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/2405.00263.json

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+{"paper_url": "https://huggingface.co/papers/2405.00263", "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* [TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding](https://huggingface.co/papers/2404.11912) (2024)\n* [Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting](https://huggingface.co/papers/2404.18911) (2024)\n* [Recurrent Drafter for Fast Speculative Decoding in Large Language Models](https://huggingface.co/papers/2403.09919) (2024)\n* [Parallel Decoding via Hidden Transfer for Lossless Large Language Model Acceleration](https://huggingface.co/papers/2404.12022) (2024)\n* [Accelerating Production LLMs with Combined Token/Embedding Speculators](https://huggingface.co/papers/2404.19124) (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/2405.00332.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2405.00332", "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* [Common 7B Language Models Already Possess Strong Math Capabilities](https://huggingface.co/papers/2403.04706) (2024)\n* [MathScale: Scaling Instruction Tuning for Mathematical Reasoning](https://huggingface.co/papers/2403.02884) (2024)\n* [FineMath: A Fine-Grained Mathematical Evaluation Benchmark for Chinese Large Language Models](https://huggingface.co/papers/2403.07747) (2024)\n* [Can LLMs Master Math? Investigating Large Language Models on Math Stack Exchange](https://huggingface.co/papers/2404.00344) (2024)\n* [How Much are LLMs Contaminated? A Comprehensive Survey and the LLMSanitize Library](https://huggingface.co/papers/2404.00699) (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/2405.00664.json

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+{"paper_url": "https://huggingface.co/papers/2405.00664", "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* [A Unified Framework for Model Editing](https://huggingface.co/papers/2403.14236) (2024)\n* [Rebuilding ROME : Resolving Model Collapse during Sequential Model Editing](https://huggingface.co/papers/2403.07175) (2024)\n* [Consecutive Model Editing with Batch alongside HooK Layers](https://huggingface.co/papers/2403.05330) (2024)\n* [Robust and Scalable Model Editing for Large Language Models](https://huggingface.co/papers/2403.17431) (2024)\n* [The Missing Piece in Model Editing: A Deep Dive into the Hidden Damage Brought By Model Editing](https://huggingface.co/papers/2403.07825) (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/2405.00675.json

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+{"paper_url": "https://huggingface.co/papers/2405.00675", "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* [Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences](https://huggingface.co/papers/2404.03715) (2024)\n* [Investigating Regularization of Self-Play Language Models](https://huggingface.co/papers/2404.04291) (2024)\n* [Token-level Direct Preference Optimization](https://huggingface.co/papers/2404.11999) (2024)\n* [Human Alignment of Large Language Models through Online Preference Optimisation](https://huggingface.co/papers/2403.08635) (2024)\n* [DPO Meets PPO: Reinforced Token Optimization for RLHF](https://huggingface.co/papers/2404.18922) (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/2405.00676.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2405.00676", "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* [RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS](https://huggingface.co/papers/2403.13806) (2024)\n* [Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians](https://huggingface.co/papers/2403.14166) (2024)\n* [FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization](https://huggingface.co/papers/2403.06908) (2024)\n* [SRGS: Super-Resolution 3D Gaussian Splatting](https://huggingface.co/papers/2404.10318) (2024)\n* [EfficientGS: Streamlining Gaussian Splatting for Large-Scale High-Resolution Scene Representation](https://huggingface.co/papers/2404.12777) (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`"}