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data/2411.07641.json

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+{"paper_url": "https://huggingface.co/papers/2411.07641", "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* [Adaptive Decoding via Latent Preference Optimization](https://huggingface.co/papers/2411.09661) (2024)\n* [Quasi-random Multi-Sample Inference for Large Language Models](https://huggingface.co/papers/2411.06251) (2024)\n* [SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models](https://huggingface.co/papers/2411.02433) (2024)\n* [AdaEDL: Early Draft Stopping for Speculative Decoding of Large Language Models via an Entropy-based Lower Bound on Token Acceptance Probability](https://huggingface.co/papers/2410.18351) (2024)\n* [Dynamic-Width Speculative Beam Decoding for Efficient LLM Inference](https://huggingface.co/papers/2409.16560) (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/2411.09213.json

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+{"paper_url": "https://huggingface.co/papers/2411.09213", "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* [Toward Optimal Search and Retrieval for RAG](https://huggingface.co/papers/2411.07396) (2024)\n* [Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models](https://huggingface.co/papers/2411.07820) (2024)\n* [Exploring Hint Generation Approaches in Open-Domain Question Answering](https://huggingface.co/papers/2409.16096) (2024)\n* [IRSC: A Zero-shot Evaluation Benchmark for Information Retrieval through Semantic Comprehension in Retrieval-Augmented Generation Scenarios](https://huggingface.co/papers/2409.15763) (2024)\n* [Leveraging Retrieval-Augmented Generation for University Knowledge Retrieval](https://huggingface.co/papers/2411.06237) (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/2411.09661.json

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+{"paper_url": "https://huggingface.co/papers/2411.09661", "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* [Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation](https://huggingface.co/papers/2410.02725) (2024)\n* [SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks](https://huggingface.co/papers/2410.05102) (2024)\n* [PAD: Personalized Alignment of LLMs at Decoding-Time](https://huggingface.co/papers/2410.04070) (2024)\n* [Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding](https://huggingface.co/papers/2411.04282) (2024)\n* [Self-supervised Preference Optimization: Enhance Your Language Model with Preference Degree Awareness](https://huggingface.co/papers/2409.17791) (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/2411.09944.json

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+{"paper_url": "https://huggingface.co/papers/2411.09944", "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* [PhoneLM:an Efficient and Capable Small Language Model Family through Principled Pre-training](https://huggingface.co/papers/2411.05046) (2024)\n* [A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://huggingface.co/papers/2411.03350) (2024)\n* [Small Language Models: Survey, Measurements, and Insights](https://huggingface.co/papers/2409.15790) (2024)\n* [Improving In-Context Learning with Small Language Model Ensembles](https://huggingface.co/papers/2410.21868) (2024)\n* [Stacking Small Language Models for Generalizability](https://huggingface.co/papers/2410.15570) (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/2411.10168.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.10168", "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\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/2411.10499.json

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+{"paper_url": "https://huggingface.co/papers/2411.10499", "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* [DH-VTON: Deep Text-Driven Virtual Try-On via Hybrid Attention Learning](https://huggingface.co/papers/2410.12501) (2024)\n* [GS-VTON: Controllable 3D Virtual Try-on with Gaussian Splatting](https://huggingface.co/papers/2410.05259) (2024)\n* [MagicEraser: Erasing Any Objects via Semantics-Aware Control](https://huggingface.co/papers/2410.10207) (2024)\n* [FashionR2R: Texture-preserving Rendered-to-Real Image Translation with Diffusion Models](https://huggingface.co/papers/2410.14429) (2024)\n* [TextCtrl: Diffusion-based Scene Text Editing with Prior Guidance Control](https://huggingface.co/papers/2410.10133) (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/2411.10510.json

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+{"paper_url": "https://huggingface.co/papers/2411.10510", "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* [FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality](https://huggingface.co/papers/2410.19355) (2024)\n* [Token Caching for Diffusion Transformer Acceleration](https://huggingface.co/papers/2409.18523) (2024)\n* [Accelerating Diffusion Transformers with Token-wise Feature Caching](https://huggingface.co/papers/2410.05317) (2024)\n* [Fast and Memory-Efficient Video Diffusion Using Streamlined Inference](https://huggingface.co/papers/2411.01171) (2024)\n* [HarmoniCa: Harmonizing Training and Inference for Better Feature Cache in Diffusion Transformer Acceleration](https://huggingface.co/papers/2410.01723) (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/2411.10640.json

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+{"paper_url": "https://huggingface.co/papers/2411.10640", "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* [SlimLM: An Efficient Small Language Model for On-Device Document Assistance](https://huggingface.co/papers/2411.09944) (2024)\n* [A Survey of Low-bit Large Language Models: Basics, Systems, and Algorithms](https://huggingface.co/papers/2409.16694) (2024)\n* [GWQ: Gradient-Aware Weight Quantization for Large Language Models](https://huggingface.co/papers/2411.00850) (2024)\n* [Toward Democratized Generative AI in Next-Generation Mobile Edge Networks](https://huggingface.co/papers/2411.09148) (2024)\n* [PhoneLM:an Efficient and Capable Small Language Model Family through Principled Pre-training](https://huggingface.co/papers/2411.05046) (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/2411.10669.json

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+{"paper_url": "https://huggingface.co/papers/2411.10669", "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* [Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training](https://huggingface.co/papers/2410.08202) (2024)\n* [MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning](https://huggingface.co/papers/2410.09437) (2024)\n* [Infinity-MM: Scaling Multimodal Performance with Large-Scale and High-Quality Instruction Data](https://huggingface.co/papers/2410.18558) (2024)\n* [MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning](https://huggingface.co/papers/2409.20566) (2024)\n* [Multimodal Instruction Tuning with Hybrid State Space Models](https://huggingface.co/papers/2411.08840) (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/2411.10836.json

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+{"paper_url": "https://huggingface.co/papers/2411.10836", "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* [Motion Control for Enhanced Complex Action Video Generation](https://huggingface.co/papers/2411.08328) (2024)\n* [LumiSculpt: A Consistency Lighting Control Network for Video Generation](https://huggingface.co/papers/2410.22979) (2024)\n* [EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation](https://huggingface.co/papers/2411.08380) (2024)\n* [ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning](https://huggingface.co/papers/2411.05003) (2024)\n* [MikuDance: Animating Character Art with Mixed Motion Dynamics](https://huggingface.co/papers/2411.08656) (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/2411.11024.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.11024", "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* [MiraGe: Editable 2D Images using Gaussian Splatting](https://huggingface.co/papers/2410.01521) (2024)\n* [Grid4D: 4D Decomposed Hash Encoding for High-fidelity Dynamic Gaussian Splatting](https://huggingface.co/papers/2410.20815) (2024)\n* [DaRePlane: Direction-aware Representations for Dynamic Scene Reconstruction](https://huggingface.co/papers/2410.14169) (2024)\n* [Disco4D: Disentangled 4D Human Generation and Animation from a Single Image](https://huggingface.co/papers/2409.17280) (2024)\n* [Fully Explicit Dynamic Gaussian Splatting](https://huggingface.co/papers/2410.15629) (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/2411.11045.json

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+{"paper_url": "https://huggingface.co/papers/2411.11045", "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* [FreeMask: Rethinking the Importance of Attention Masks for Zero-Shot Video Editing](https://huggingface.co/papers/2409.20500) (2024)\n* [Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models](https://huggingface.co/papers/2410.10821) (2024)\n* [Shaping a Stabilized Video by Mitigating Unintended Changes for Concept-Augmented Video Editing](https://huggingface.co/papers/2410.12526) (2024)\n* [TextCtrl: Diffusion-based Scene Text Editing with Prior Guidance Control](https://huggingface.co/papers/2410.10133) (2024)\n* [Generative Object Insertion in Gaussian Splatting with a Multi-View Diffusion Model](https://huggingface.co/papers/2409.16938) (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/2411.11171.json

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+{"paper_url": "https://huggingface.co/papers/2411.11171", "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* [EuroLLM: Multilingual Language Models for Europe](https://huggingface.co/papers/2409.16235) (2024)\n* [SAG: Style-Aligned Article Generation via Model Collaboration](https://huggingface.co/papers/2410.03137) (2024)\n* [Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language](https://huggingface.co/papers/2410.23956) (2024)\n* [Xmodel-1.5: An 1B-scale Multilingual LLM](https://huggingface.co/papers/2411.10083) (2024)\n* [Adapting Multilingual LLMs to Low-Resource Languages using Continued Pre-training and Synthetic Corpus](https://huggingface.co/papers/2410.14815) (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/2411.11504.json

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+{"paper_url": "https://huggingface.co/papers/2411.11504", "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* [Improving LLM Reasoning through Scaling Inference Computation with Collaborative Verification](https://huggingface.co/papers/2410.05318) (2024)\n* [Forewarned is Forearmed: Leveraging LLMs for Data Synthesis through Failure-Inducing Exploration](https://huggingface.co/papers/2410.16736) (2024)\n* [Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment](https://huggingface.co/papers/2410.14148) (2024)\n* [Deliberate Reasoning for LLMs as Structure-aware Planning with Accurate World Model](https://huggingface.co/papers/2410.03136) (2024)\n* [Process Supervision-Guided Policy Optimization for Code Generation](https://huggingface.co/papers/2410.17621) (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/2411.11767.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.11767", "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* [Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback](https://huggingface.co/papers/2410.21242) (2024)\n* [JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking](https://huggingface.co/papers/2411.00142) (2024)\n* [An Early FIRST Reproduction and Improvements to Single-Token Decoding for Fast Listwise Reranking](https://huggingface.co/papers/2411.05508) (2024)\n* [RARe: Retrieval Augmented Retrieval with In-Context Examples](https://huggingface.co/papers/2410.20088) (2024)\n* [Few-shot Prompting for Pairwise Ranking: An Effective Non-Parametric Retrieval Model](https://huggingface.co/papers/2409.17745) (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/2411.11844.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.11844", "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* [Grounding Large Language Models In Embodied Environment With Imperfect World Models](https://huggingface.co/papers/2410.02742) (2024)\n* [ImagineNav: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination](https://huggingface.co/papers/2410.09874) (2024)\n* [GAN Based Top-Down View Synthesis in Reinforcement Learning Environments](https://huggingface.co/papers/2410.12372) (2024)\n* [ReLEP: A Novel Framework for Real-world Long-horizon Embodied Planning](https://huggingface.co/papers/2409.15658) (2024)\n* [Spatial Reasoning and Planning for Deep Embodied Agents](https://huggingface.co/papers/2409.19479) (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`"}