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data/2409.08425.json

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+{"paper_url": "https://huggingface.co/papers/2409.08425", "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* [EzAudio: Enhancing Text-to-Audio Generation with Efficient Diffusion Transformer](https://huggingface.co/papers/2409.10819) (2024)\n* [Sample-Efficient Diffusion for Text-To-Speech Synthesis](https://huggingface.co/papers/2409.03717) (2024)\n* [FlowSep: Language-Queried Sound Separation with Rectified Flow Matching](https://huggingface.co/papers/2409.07614) (2024)\n* [MambaFoley: Foley Sound Generation using Selective State-Space Models](https://huggingface.co/papers/2409.09162) (2024)\n* [Out-Of-Distribution Detection for Audio-visual Generalized Zero-Shot Learning: A General Framework](https://huggingface.co/papers/2408.01284) (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/2409.09401.json

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+{"paper_url": "https://huggingface.co/papers/2409.09401", "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* [EnCLAP++: Analyzing the EnCLAP Framework for Optimizing Automated Audio Captioning Performance](https://huggingface.co/papers/2409.01201) (2024)\n* [Expanding on EnCLAP with Auxiliary Retrieval Model for Automated Audio Captioning](https://huggingface.co/papers/2409.01160) (2024)\n* [VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling](https://huggingface.co/papers/2408.01181) (2024)\n* [EzAudio: Enhancing Text-to-Audio Generation with Efficient Diffusion Transformer](https://huggingface.co/papers/2409.10819) (2024)\n* [UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation](https://huggingface.co/papers/2408.11305) (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/2409.11564.json

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+{"paper_url": "https://huggingface.co/papers/2409.11564", "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* [RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data](https://huggingface.co/papers/2408.12109) (2024)\n* [TSO: Self-Training with Scaled Preference Optimization](https://huggingface.co/papers/2409.02118) (2024)\n* [ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning](https://huggingface.co/papers/2408.03402) (2024)\n* [MoExtend: Tuning New Experts for Modality and Task Extension](https://huggingface.co/papers/2408.03511) (2024)\n* [Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities](https://huggingface.co/papers/2409.03444) (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/2409.11733.json

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+{"paper_url": "https://huggingface.co/papers/2409.11733", "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* [GPT-4 Emulates Average-Human Emotional Cognition from a Third-Person Perspective](https://huggingface.co/papers/2408.13718) (2024)\n* [Knowledge-based Emotion Recognition using Large Language Models](https://huggingface.co/papers/2408.04123) (2024)\n* [Towards a Generative Approach for Emotion Detection and Reasoning](https://huggingface.co/papers/2408.04906) (2024)\n* [ExpLLM: Towards Chain of Thought for Facial Expression Recognition](https://huggingface.co/papers/2409.02828) (2024)\n* [Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective](https://huggingface.co/papers/2408.04638) (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/2409.12001.json

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+{"paper_url": "https://huggingface.co/papers/2409.12001", "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* [Diffusion-based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning](https://huggingface.co/papers/2408.13092) (2024)\n* [Multi-Agent Reinforcement Learning from Human Feedback: Data Coverage and Algorithmic Techniques](https://huggingface.co/papers/2409.00717) (2024)\n* [Hybrid Training for Enhanced Multi-task Generalization in Multi-agent Reinforcement Learning](https://huggingface.co/papers/2408.13567) (2024)\n* [D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning](https://huggingface.co/papers/2408.08441) (2024)\n* [Domain Adaptation for Offline Reinforcement Learning with Limited Samples](https://huggingface.co/papers/2408.12136) (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/2409.12136.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2409.12136", "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* [LaDiMo: Layer-wise Distillation Inspired MoEfier](https://huggingface.co/papers/2408.04278) (2024)\n* [Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning](https://huggingface.co/papers/2409.01483) (2024)\n* [HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou](https://huggingface.co/papers/2408.05430) (2024)\n* [BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts](https://huggingface.co/papers/2408.08274) (2024)\n* [Nexus: Specialization meets Adaptability for Efficiently Training Mixture of Experts](https://huggingface.co/papers/2408.15901) (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/2409.12139.json

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+{"paper_url": "https://huggingface.co/papers/2409.12139", "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* [FireRedTTS: A Foundation Text-To-Speech Framework for Industry-Level Generative Speech Applications](https://huggingface.co/papers/2409.03283) (2024)\n* [SSL-TTS: Leveraging Self-Supervised Embeddings and kNN Retrieval for Zero-Shot Multi-speaker TTS](https://huggingface.co/papers/2408.10771) (2024)\n* [Disentangling the Prosody and Semantic Information with Pre-trained Model for In-Context Learning based Zero-Shot Voice Conversion](https://huggingface.co/papers/2409.05004) (2024)\n* [StyleTTS-ZS: Efficient High-Quality Zero-Shot Text-to-Speech Synthesis with Distilled Time-Varying Style Diffusion](https://huggingface.co/papers/2409.10058) (2024)\n* [AS-Speech: Adaptive Style For Speech Synthesis](https://huggingface.co/papers/2409.05730) (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/2409.12181.json

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+{"paper_url": "https://huggingface.co/papers/2409.12181", "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* [LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models](https://huggingface.co/papers/2409.00509) (2024)\n* [Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models](https://huggingface.co/papers/2409.04774) (2024)\n* [E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning](https://huggingface.co/papers/2409.06679) (2024)\n* [FocusLLM: Scaling LLM's Context by Parallel Decoding](https://huggingface.co/papers/2408.11745) (2024)\n* [MemLong: Memory-Augmented Retrieval for Long Text Modeling](https://huggingface.co/papers/2408.16967) (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/2409.12193.json

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+{"paper_url": "https://huggingface.co/papers/2409.12193", "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* [Localized Gaussian Splatting Editing with Contextual Awareness](https://huggingface.co/papers/2408.00083) (2024)\n* [MeTTA: Single-View to 3D Textured Mesh Reconstruction with Test-Time Adaptation](https://huggingface.co/papers/2408.11465) (2024)\n* [ScalingGaussian: Enhancing 3D Content Creation with Generative Gaussian Splatting](https://huggingface.co/papers/2407.19035) (2024)\n* [DreamDissector: Learning Disentangled Text-to-3D Generation from 2D Diffusion Priors](https://huggingface.co/papers/2407.16260) (2024)\n* [SpaRP: Fast 3D Object Reconstruction and Pose Estimation from Sparse Views](https://huggingface.co/papers/2408.10195) (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`"}