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data/2408.07852.json

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+{"paper_url": "https://huggingface.co/papers/2408.07852", "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* [Banishing LLM Hallucinations Requires Rethinking Generalization](https://huggingface.co/papers/2406.17642) (2024)\n* [Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models](https://huggingface.co/papers/2407.08039) (2024)\n* [Leveraging Graph Structures to Detect Hallucinations in Large Language Models](https://huggingface.co/papers/2407.04485) (2024)\n* [Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps](https://huggingface.co/papers/2407.07071) (2024)\n* [GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework](https://huggingface.co/papers/2407.10793) (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/2408.07990.json

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+{"paper_url": "https://huggingface.co/papers/2408.07990", "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* [ProFuser: Progressive Fusion of Large Language Models](https://huggingface.co/papers/2408.04998) (2024)\n* [Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models](https://huggingface.co/papers/2407.06089) (2024)\n* [Extend Model Merging from Fine-Tuned to Pre-Trained Large Language Models via Weight Disentanglement](https://huggingface.co/papers/2408.03092) (2024)\n* [Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment](https://huggingface.co/papers/2407.10804) (2024)\n* [Self-Prompt Tuning: Enable Autonomous Role-Playing in LLMs](https://huggingface.co/papers/2407.08995) (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/2408.08000.json

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+{"paper_url": "https://huggingface.co/papers/2408.08000", "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* [Scene123: One Prompt to 3D Scene Generation via Video-Assisted and Consistency-Enhanced MAE](https://huggingface.co/papers/2408.05477) (2024)\n* [Animate3D: Animating Any 3D Model with Multi-view Video Diffusion](https://huggingface.co/papers/2407.11398) (2024)\n* [SyncNoise: Geometrically Consistent Noise Prediction for Text-based 3D Scene Editing](https://huggingface.co/papers/2406.17396) (2024)\n* [Localized Gaussian Splatting Editing with Contextual Awareness](https://huggingface.co/papers/2408.00083) (2024)\n* [GenRC: Generative 3D Room Completion from Sparse Image Collections](https://huggingface.co/papers/2407.12939) (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/2408.08019.json

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+{"paper_url": "https://huggingface.co/papers/2408.08019", "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* [VNet: A GAN-based Multi-Tier Discriminator Network for Speech Synthesis Vocoders](https://huggingface.co/papers/2408.06906) (2024)\n* [FA-GAN: Artifacts-free and Phase-aware High-fidelity GAN-based Vocoder](https://huggingface.co/papers/2407.04575) (2024)\n* [Improving Unsupervised Clean-to-Rendered Guitar Tone Transformation Using GANs and Integrated Unaligned Clean Data](https://huggingface.co/papers/2406.15751) (2024)\n* [FLY-TTS: Fast, Lightweight and High-Quality End-to-End Text-to-Speech Synthesis](https://huggingface.co/papers/2407.00753) (2024)\n* [Accelerating Diffusion for SAR-to-Optical Image Translation via Adversarial Consistency Distillation](https://huggingface.co/papers/2407.06095) (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/2408.08072.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08072", "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* [FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only](https://huggingface.co/papers/2408.01323) (2024)\n* [Synthesizing Text-to-SQL Data from Weak and Strong LLMs](https://huggingface.co/papers/2408.03256) (2024)\n* [Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models](https://huggingface.co/papers/2406.13542) (2024)\n* [SELF-GUIDE: Better Task-Specific Instruction Following via Self-Synthetic Finetuning](https://huggingface.co/papers/2407.12874) (2024)\n* [Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge](https://huggingface.co/papers/2407.19594) (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/2408.08152.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08152", "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* [Lean-STaR: Learning to Interleave Thinking and Proving](https://huggingface.co/papers/2407.10040) (2024)\n* [LEAN-GitHub: Compiling GitHub LEAN repositories for a versatile LEAN prover](https://huggingface.co/papers/2407.17227) (2024)\n* [TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts](https://huggingface.co/papers/2407.03203) (2024)\n* [Towards Automated Functional Equation Proving: A Benchmark Dataset and A Domain-Specific In-Context Agent](https://huggingface.co/papers/2407.14521) (2024)\n* [Large Language Model for Verilog Generation with Golden Code Feedback](https://huggingface.co/papers/2407.18271) (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/2408.08172.json

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+{"paper_url": "https://huggingface.co/papers/2408.08172", "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* [Continually Learn to Map Visual Concepts to Large Language Models in Resource-constrained Environments](https://huggingface.co/papers/2407.08279) (2024)\n* [Accessing Vision Foundation Models at ImageNet-level Costs](https://huggingface.co/papers/2407.10366) (2024)\n* [Exploiting the Semantic Knowledge of Pre-trained Text-Encoders for Continual Learning](https://huggingface.co/papers/2408.01076) (2024)\n* [Imperfect Vision Encoders: Efficient and Robust Tuning for Vision-Language Models](https://huggingface.co/papers/2407.16526) (2024)\n* [NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning](https://huggingface.co/papers/2407.08672) (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/2408.08189.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08189", "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* [VIMI: Grounding Video Generation through Multi-modal Instruction](https://huggingface.co/papers/2407.06304) (2024)\n* [VEnhancer: Generative Space-Time Enhancement for Video Generation](https://huggingface.co/papers/2407.07667) (2024)\n* [FoleyCrafter: Bring Silent Videos to Life with Lifelike and Synchronized Sounds](https://huggingface.co/papers/2407.01494) (2024)\n* [OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation](https://huggingface.co/papers/2407.02371) (2024)\n* [GVDIFF: Grounded Text-to-Video Generation with Diffusion Models](https://huggingface.co/papers/2407.01921) (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/2408.08201.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08201", "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* [SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning](https://huggingface.co/papers/2407.03036) (2024)\n* [Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator](https://huggingface.co/papers/2408.06927) (2024)\n* [Fully Fine-tuned CLIP Models are Efficient Few-Shot Learners](https://huggingface.co/papers/2407.04003) (2024)\n* [Learn to Preserve and Diversify: Parameter-Efficient Group with Orthogonal Regularization for Domain Generalization](https://huggingface.co/papers/2407.15085) (2024)\n* [Efficient and Versatile Robust Fine-Tuning of Zero-shot Models](https://huggingface.co/papers/2408.05749) (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/2408.08274.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08274", "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* [LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training](https://huggingface.co/papers/2406.16554) (2024)\n* [A Survey on Mixture of Experts](https://huggingface.co/papers/2407.06204) (2024)\n* [Layerwise Recurrent Router for Mixture-of-Experts](https://huggingface.co/papers/2408.06793) (2024)\n* [AdaMoE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models](https://huggingface.co/papers/2406.13233) (2024)\n* [MaskMoE: Boosting Token-Level Learning via Routing Mask in Mixture-of-Experts](https://huggingface.co/papers/2407.09816) (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/2408.08291.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08291", "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* [Role-Play Zero-Shot Prompting with Large Language Models for Open-Domain Human-Machine Conversation](https://huggingface.co/papers/2406.18460) (2024)\n* [ProxyGPT: Enabling Anonymous Queries in AI Chatbots with (Un)Trustworthy Browser Proxies](https://huggingface.co/papers/2407.08792) (2024)\n* [BotEval: Facilitating Interactive Human Evaluation](https://huggingface.co/papers/2407.17770) (2024)\n* [Conversational Prompt Engineering](https://huggingface.co/papers/2408.04560) (2024)\n* [LEXI: Large Language Models Experimentation Interface](https://huggingface.co/papers/2407.01488) (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/2408.08313.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.08313", "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* [Losing Visual Needles in Image Haystacks: Vision Language Models are Easily Distracted in Short and Long Contexts](https://huggingface.co/papers/2406.16851) (2024)\n* [Pyramid Coder: Hierarchical Code Generator for Compositional Visual Question Answering](https://huggingface.co/papers/2407.20563) (2024)\n* [Large Language Models Understand Layout](https://huggingface.co/papers/2407.05750) (2024)\n* [GlyphPattern: An Abstract Pattern Recognition for Vision-Language Models](https://huggingface.co/papers/2408.05894) (2024)\n* [Revisiting Multi-Modal LLM Evaluation](https://huggingface.co/papers/2408.05334) (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`"}