Scheduled Commit

data/2404.19149.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19149", "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* [GSDF: 3DGS Meets SDF for Improved Rendering and Reconstruction](https://huggingface.co/papers/2403.16964) (2024)\n* [HO-Gaussian: Hybrid Optimization of 3D Gaussian Splatting for Urban Scenes](https://huggingface.co/papers/2403.20032) (2024)\n* [Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians](https://huggingface.co/papers/2403.17898) (2024)\n* [AbsGS: Recovering Fine Details for 3D Gaussian Splatting](https://huggingface.co/papers/2404.10484) (2024)\n* [RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS](https://huggingface.co/papers/2403.13806) (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/2404.19296.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19296", "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* [Telecom Language Models: Must They Be Large?](https://huggingface.co/papers/2403.04666) (2024)\n* [ChatGPT Alternative Solutions: Large Language Models Survey](https://huggingface.co/papers/2403.14469) (2024)\n* [Improving the Capabilities of Large Language Model based Marketing Analytics Copilots with Semantic Search and Fine-Tuning](https://huggingface.co/papers/2404.13077) (2024)\n* [A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applications](https://huggingface.co/papers/2404.14809) (2024)\n* [Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks](https://huggingface.co/papers/2404.00376) (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/2404.19427.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19427", "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* [IDAdapter: Learning Mixed Features for Tuning-Free Personalization of Text-to-Image Models](https://huggingface.co/papers/2403.13535) (2024)\n* [Infinite-ID: Identity-preserved Personalization via ID-semantics Decoupling Paradigm](https://huggingface.co/papers/2403.11781) (2024)\n* [From Parts to Whole: A Unified Reference Framework for Controllable Human Image Generation](https://huggingface.co/papers/2404.15267) (2024)\n* [ConsistentID: Portrait Generation with Multimodal Fine-Grained Identity Preserving](https://huggingface.co/papers/2404.16771) (2024)\n* [ID-Animator: Zero-Shot Identity-Preserving Human Video Generation](https://huggingface.co/papers/2404.15275) (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/2404.19525.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19525", "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* [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://huggingface.co/papers/2403.10395) (2024)\n* [Magic-Boost: Boost 3D Generation with Mutli-View Conditioned Diffusion](https://huggingface.co/papers/2404.06429) (2024)\n* [Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting](https://huggingface.co/papers/2403.09981) (2024)\n* [V3D: Video Diffusion Models are Effective 3D Generators](https://huggingface.co/papers/2403.06738) (2024)\n* [InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models](https://huggingface.co/papers/2404.07191) (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/2404.19553.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19553", "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* [Make Your LLM Fully Utilize the Context](https://huggingface.co/papers/2404.16811) (2024)\n* [LLoCO: Learning Long Contexts Offline](https://huggingface.co/papers/2404.07979) (2024)\n* [Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks](https://huggingface.co/papers/2404.06480) (2024)\n* [Long-context LLMs Struggle with Long In-context Learning](https://huggingface.co/papers/2404.02060) (2024)\n* [LongEmbed: Extending Embedding Models for Long Context Retrieval](https://huggingface.co/papers/2404.12096) (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/2404.19702.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19702", "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* [MeshLRM: Large Reconstruction Model for High-Quality Mesh](https://huggingface.co/papers/2404.12385) (2024)\n* [GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation](https://huggingface.co/papers/2403.14621) (2024)\n* [MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images](https://huggingface.co/papers/2403.14627) (2024)\n* [latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction](https://huggingface.co/papers/2403.16292) (2024)\n* [InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models](https://huggingface.co/papers/2404.07191) (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/2404.19733.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19733", "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* [Self-Explore to Avoid the Pit: Improving the Reasoning Capabilities of Language Models with Fine-grained Rewards](https://huggingface.co/papers/2404.10346) (2024)\n* [Improving Language Model Reasoning with Self-motivated Learning](https://huggingface.co/papers/2404.07017) (2024)\n* [Advancing LLM Reasoning Generalists with Preference Trees](https://huggingface.co/papers/2404.02078) (2024)\n* [Teaching Large Language Models to Reason with Reinforcement Learning](https://huggingface.co/papers/2403.04642) (2024)\n* [Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision](https://huggingface.co/papers/2403.09472) (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/2404.19752.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19752", "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 the Distinctiveness and Fidelity of the Descriptions Generated by Large Vision-Language Models](https://huggingface.co/papers/2404.17534) (2024)\n* [View Selection for 3D Captioning via Diffusion Ranking](https://huggingface.co/papers/2404.07984) (2024)\n* [Enhancing Visual Question Answering through Question-Driven Image Captions as Prompts](https://huggingface.co/papers/2404.08589) (2024)\n* [The Solution for the CVPR2024 NICE Image Captioning Challenge](https://huggingface.co/papers/2404.12739) (2024)\n* [FlexCap: Generating Rich, Localized, and Flexible Captions in Images](https://huggingface.co/papers/2403.12026) (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/2404.19753.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19753", "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* [Getting it Right: Improving Spatial Consistency in Text-to-Image Models](https://huggingface.co/papers/2404.01197) (2024)\n* [Evaluating Text-to-Visual Generation with Image-to-Text Generation](https://huggingface.co/papers/2404.01291) (2024)\n* [Exploring the Distinctiveness and Fidelity of the Descriptions Generated by Large Vision-Language Models](https://huggingface.co/papers/2404.17534) (2024)\n* [FlexCap: Generating Rich, Localized, and Flexible Captions in Images](https://huggingface.co/papers/2403.12026) (2024)\n* [Revisiting Text-to-Image Evaluation with Gecko: On Metrics, Prompts, and Human Ratings](https://huggingface.co/papers/2404.16820) (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/2404.19758.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19758", "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* [RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion](https://huggingface.co/papers/2404.07199) (2024)\n* [InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Prior](https://huggingface.co/papers/2404.11613) (2024)\n* [DreamScene360: Unconstrained Text-to-3D Scene Generation with Panoramic Gaussian Splatting](https://huggingface.co/papers/2404.06903) (2024)\n* [DepthFM: Fast Monocular Depth Estimation with Flow Matching](https://huggingface.co/papers/2403.13788) (2024)\n* [Diffusion Models are Geometry Critics: Single Image 3D Editing Using Pre-Trained Diffusion Priors](https://huggingface.co/papers/2403.11503) (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/2404.19759.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19759", "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 Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM](https://huggingface.co/papers/2403.07487) (2024)\n* [BAMM: Bidirectional Autoregressive Motion Model](https://huggingface.co/papers/2403.19435) (2024)\n* [Accelerating Image Generation with Sub-path Linear Approximation Model](https://huggingface.co/papers/2404.13903) (2024)\n* [MotionChain: Conversational Motion Controllers via Multimodal Prompts](https://huggingface.co/papers/2404.01700) (2024)\n* [CoMo: Controllable Motion Generation through Language Guided Pose Code Editing](https://huggingface.co/papers/2403.13900) (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/2404.19760.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.19760", "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* [6Img-to-3D: Few-Image Large-Scale Outdoor Driving Scene Reconstruction](https://huggingface.co/papers/2404.12378) (2024)\n* [INPC: Implicit Neural Point Clouds for Radiance Field Rendering](https://huggingface.co/papers/2403.16862) (2024)\n* [LN3Diff: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation](https://huggingface.co/papers/2403.12019) (2024)\n* [Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications](https://huggingface.co/papers/2403.11131) (2024)\n* [GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond](https://huggingface.co/papers/2403.19632) (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`"}