Scheduled Commit

data/2404.05902.json

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+{"paper_url": "https://huggingface.co/papers/2404.05902", "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* [AutoGuide: Automated Generation and Selection of State-Aware Guidelines for Large Language Model Agents](https://huggingface.co/papers/2403.08978) (2024)\n* [BAGEL: Bootstrapping Agents by Guiding Exploration with Language](https://huggingface.co/papers/2403.08140) (2024)\n* [Autonomous Evaluation and Refinement of Digital Agents](https://huggingface.co/papers/2404.06474) (2024)\n* [AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent](https://huggingface.co/papers/2404.03648) (2024)\n* [TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned Decision](https://huggingface.co/papers/2403.06221) (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/2404.06654.json

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+{"paper_url": "https://huggingface.co/papers/2404.06654", "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* [Long-context LLMs Struggle with Long In-context Learning](https://huggingface.co/papers/2404.02060) (2024)\n* [\u221eBench: Extending Long Context Evaluation Beyond 100K Tokens](https://huggingface.co/papers/2402.13718) (2024)\n* [Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks](https://huggingface.co/papers/2404.06480) (2024)\n* [CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models](https://huggingface.co/papers/2403.03514) (2024)\n* [NovelQA: A Benchmark for Long-Range Novel Question Answering](https://huggingface.co/papers/2403.12766) (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/2404.06773.json

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+{"paper_url": "https://huggingface.co/papers/2404.06773", "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* [VisionLLaMA: A Unified LLaMA Interface for Vision Tasks](https://huggingface.co/papers/2403.00522) (2024)\n* [Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach](https://huggingface.co/papers/2403.19067) (2024)\n* [MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations](https://huggingface.co/papers/2402.10093) (2024)\n* [GiT: Towards Generalist Vision Transformer through Universal Language Interface](https://huggingface.co/papers/2403.09394) (2024)\n* [Improved Baselines for Data-efficient Perceptual Augmentation of LLMs](https://huggingface.co/papers/2403.13499) (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/2404.06780.json

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+{"paper_url": "https://huggingface.co/papers/2404.06780", "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* [DreamPolisher: Towards High-Quality Text-to-3D Generation via Geometric Diffusion](https://huggingface.co/papers/2403.17237) (2024)\n* [Urban Scene Diffusion through Semantic Occupancy Map](https://huggingface.co/papers/2403.11697) (2024)\n* [Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting](https://huggingface.co/papers/2403.09981) (2024)\n* [DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Sampling](https://huggingface.co/papers/2404.03575) (2024)\n* [RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion](https://huggingface.co/papers/2404.07199) (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/2404.06903.json

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+{"paper_url": "https://huggingface.co/papers/2404.06903", "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* [Comp4D: LLM-Guided Compositional 4D Scene Generation](https://huggingface.co/papers/2403.16993) (2024)\n* [DreamPolisher: Towards High-Quality Text-to-3D Generation via Geometric Diffusion](https://huggingface.co/papers/2403.17237) (2024)\n* [DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Sampling](https://huggingface.co/papers/2404.03575) (2024)\n* [InstantSplat: Unbounded Sparse-view Pose-free Gaussian Splatting in 40 Seconds](https://huggingface.co/papers/2403.20309) (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/2404.07143.json

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+{"paper_url": "https://huggingface.co/papers/2404.07143", "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* [Long-Context Language Modeling with Parallel Context Encoding](https://huggingface.co/papers/2402.16617) (2024)\n* [LongHeads: Multi-Head Attention is Secretly a Long Context Processor](https://huggingface.co/papers/2402.10685) (2024)\n* [CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory](https://huggingface.co/papers/2402.13449) (2024)\n* [Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference](https://huggingface.co/papers/2403.09636) (2024)\n* [Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models](https://huggingface.co/papers/2402.19427) (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/2404.07199.json

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+{"paper_url": "https://huggingface.co/papers/2404.07199", "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* [DreamScene360: Unconstrained Text-to-3D Scene Generation with Panoramic Gaussian Splatting](https://huggingface.co/papers/2404.06903) (2024)\n* [Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting](https://huggingface.co/papers/2403.09981) (2024)\n* [VP3D: Unleashing 2D Visual Prompt for Text-to-3D Generation](https://huggingface.co/papers/2403.17001) (2024)\n* [ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models](https://huggingface.co/papers/2403.01807) (2024)\n* [Isotropic3D: Image-to-3D Generation Based on a Single CLIP Embedding](https://huggingface.co/papers/2403.10395) (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/2404.07204.json

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+{"paper_url": "https://huggingface.co/papers/2404.07204", "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* [Improved Baselines for Data-efficient Perceptual Augmentation of LLMs](https://huggingface.co/papers/2403.13499) (2024)\n* [PaLM2-VAdapter: Progressively Aligned Language Model Makes a Strong Vision-language Adapter](https://huggingface.co/papers/2402.10896) (2024)\n* [MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training](https://huggingface.co/papers/2403.09611) (2024)\n* [Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning](https://huggingface.co/papers/2404.00909) (2024)\n* [ViTamin: Designing Scalable Vision Models in the Vision-Language Era](https://huggingface.co/papers/2404.02132) (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/2404.07448.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07448", "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* [MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric](https://huggingface.co/papers/2403.07839) (2024)\n* [Language-Driven Visual Consensus for Zero-Shot Semantic Segmentation](https://huggingface.co/papers/2403.08426) (2024)\n* [Self-Adapting Large Visual-Language Models to Edge Devices across Visual Modalities](https://huggingface.co/papers/2403.04908) (2024)\n* [PosSAM: Panoptic Open-vocabulary Segment Anything](https://huggingface.co/papers/2403.09620) (2024)\n* [Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach](https://huggingface.co/papers/2403.19067) (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/2404.07503.json

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+{"paper_url": "https://huggingface.co/papers/2404.07503", "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* [Generative AI for Synthetic Data Generation: Methods, Challenges and the Future](https://huggingface.co/papers/2403.04190) (2024)\n* [Data Augmentation using LLMs: Data Perspectives, Learning Paradigms and Challenges](https://huggingface.co/papers/2403.02990) (2024)\n* [LLMs with Industrial Lens: Deciphering the Challenges and Prospects - A Survey](https://huggingface.co/papers/2402.14558) (2024)\n* [On the Challenges and Opportunities in Generative AI](https://huggingface.co/papers/2403.00025) (2024)\n* [Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks](https://huggingface.co/papers/2402.13482) (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/2404.07544.json

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+{"paper_url": "https://huggingface.co/papers/2404.07544", "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* [LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders](https://huggingface.co/papers/2404.05961) (2024)\n* [Training Nonlinear Transformers for Efficient In-Context Learning: A Theoretical Learning and Generalization Analysis](https://huggingface.co/papers/2402.15607) (2024)\n* [Se2: Sequential Example Selection for In-Context Learning](https://huggingface.co/papers/2402.13874) (2024)\n* [Towards Understanding the Relationship between In-context Learning and Compositional Generalization](https://huggingface.co/papers/2403.11834) (2024)\n* [Emergent Abilities in Reduced-Scale Generative Language Models](https://huggingface.co/papers/2404.02204) (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/2404.07616.json

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+{"paper_url": "https://huggingface.co/papers/2404.07616", "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* [AVicuna: Audio-Visual LLM with Interleaver and Context-Boundary Alignment for Temporal Referential Dialogue](https://huggingface.co/papers/2403.16276) (2024)\n* [DialogGen: Multi-modal Interactive Dialogue System for Multi-turn Text-to-Image Generation](https://huggingface.co/papers/2403.08857) (2024)\n* [A Detailed Audio-Text Data Simulation Pipeline using Single-Event Sounds](https://huggingface.co/papers/2403.04594) (2024)\n* [Advancing Large Language Models to Capture Varied Speaking Styles and Respond Properly in Spoken Conversations](https://huggingface.co/papers/2402.12786) (2024)\n* [CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios](https://huggingface.co/papers/2403.04640) (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/2404.07724.json

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+{"paper_url": "https://huggingface.co/papers/2404.07724", "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-Rectifying Diffusion Sampling with Perturbed-Attention Guidance](https://huggingface.co/papers/2403.17377) (2024)\n* [Rethinking the Spatial Inconsistency in Classifier-Free Diffusion Guidance](https://huggingface.co/papers/2404.05384) (2024)\n* [Improving Diffusion-Based Generative Models via Approximated Optimal Transport](https://huggingface.co/papers/2403.05069) (2024)\n* [Upsample Guidance: Scale Up Diffusion Models without Training](https://huggingface.co/papers/2404.01709) (2024)\n* [ReNoise: Real Image Inversion Through Iterative Noising](https://huggingface.co/papers/2403.14602) (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/2404.07821.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07821", "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* [LDTR: Transformer-based Lane Detection with Anchor-chain Representation](https://huggingface.co/papers/2403.14354) (2024)\n* [Lane2Seq: Towards Unified Lane Detection via Sequence Generation](https://huggingface.co/papers/2402.17172) (2024)\n* [LanePtrNet: Revisiting Lane Detection as Point Voting and Grouping on Curves](https://huggingface.co/papers/2403.05155) (2024)\n* [Monocular 3D lane detection for Autonomous Driving: Recent Achievements, Challenges, and Outlooks](https://huggingface.co/papers/2404.06860) (2024)\n* [ENet-21: An Optimized light CNN Structure for Lane Detection](https://huggingface.co/papers/2403.19782) (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/2404.07839.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07839", "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* [Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models](https://huggingface.co/papers/2402.19427) (2024)\n* [Long-Context Language Modeling with Parallel Context Encoding](https://huggingface.co/papers/2402.16617) (2024)\n* [Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention](https://huggingface.co/papers/2404.07143) (2024)\n* [Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference](https://huggingface.co/papers/2403.09636) (2024)\n* [Cross-Architecture Transfer Learning for Linear-Cost Inference Transformers](https://huggingface.co/papers/2404.02684) (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/2404.07904.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07904", "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* [Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models](https://huggingface.co/papers/2402.19427) (2024)\n* [DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models](https://huggingface.co/papers/2403.00818) (2024)\n* [Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence](https://huggingface.co/papers/2404.05892) (2024)\n* [Cross-Architecture Transfer Learning for Linear-Cost Inference Transformers](https://huggingface.co/papers/2404.02684) (2024)\n* [Linear Transformers with Learnable Kernel Functions are Better In-Context Models](https://huggingface.co/papers/2402.10644) (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/2404.07972.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07972", "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* [AgentStudio: A Toolkit for Building General Virtual Agents](https://huggingface.co/papers/2403.17918) (2024)\n* [OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web](https://huggingface.co/papers/2402.17553) (2024)\n* [WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?](https://huggingface.co/papers/2403.07718) (2024)\n* [Large Multimodal Agents: A Survey](https://huggingface.co/papers/2402.15116) (2024)\n* [VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?](https://huggingface.co/papers/2404.05955) (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/2404.07973.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07973", "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* [Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-Referring](https://huggingface.co/papers/2403.09333) (2024)\n* [InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding](https://huggingface.co/papers/2403.01487) (2024)\n* [The (R)Evolution of Multimodal Large Language Models: A Survey](https://huggingface.co/papers/2402.12451) (2024)\n* [RegionGPT: Towards Region Understanding Vision Language Model](https://huggingface.co/papers/2403.02330) (2024)\n* [Visual CoT: Unleashing Chain-of-Thought Reasoning in Multi-Modal Language Models](https://huggingface.co/papers/2403.16999) (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/2404.07979.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2404.07979", "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* [Long-Context Language Modeling with Parallel Context Encoding](https://huggingface.co/papers/2402.16617) (2024)\n* [Grounding Language Model with Chunking-Free In-Context Retrieval](https://huggingface.co/papers/2402.09760) (2024)\n* [Training-Free Long-Context Scaling of Large Language Models](https://huggingface.co/papers/2402.17463) (2024)\n* [Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts](https://huggingface.co/papers/2404.02022) (2024)\n* [BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models](https://huggingface.co/papers/2402.11573) (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/2404.07987.json

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+{"paper_url": "https://huggingface.co/papers/2404.07987", "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* [UniFL: Improve Stable Diffusion via Unified Feedback Learning](https://huggingface.co/papers/2404.05595) (2024)\n* [SmartControl: Enhancing ControlNet for Handling Rough Visual Conditions](https://huggingface.co/papers/2404.06451) (2024)\n* [TextCraftor: Your Text Encoder Can be Image Quality Controller](https://huggingface.co/papers/2403.18978) (2024)\n* [DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations](https://huggingface.co/papers/2403.06951) (2024)\n* [One-Step Image Translation with Text-to-Image Models](https://huggingface.co/papers/2403.12036) (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`"}