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data/2403.19851.json

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+{"paper_url": "https://huggingface.co/papers/2403.19851", "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* [ROME: Memorization Insights from Text, Probability and Hidden State in Large Language Models](https://huggingface.co/papers/2403.00510) (2024)\n* [Interpreting Context Look-ups in Transformers: Investigating Attention-MLP Interactions](https://huggingface.co/papers/2402.15055) (2024)\n* [Token Alignment via Character Matching for Subword Completion](https://huggingface.co/papers/2403.08688) (2024)\n* [Parallel Structures in Pre-training Data Yield In-Context Learning](https://huggingface.co/papers/2402.12530) (2024)\n* [The Heuristic Core: Understanding Subnetwork Generalization in Pretrained Language Models](https://huggingface.co/papers/2403.03942) (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/2403.19887.json

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+{"paper_url": "https://huggingface.co/papers/2403.19887", "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* [DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models](https://huggingface.co/papers/2403.00818) (2024)\n* [Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference](https://huggingface.co/papers/2403.14520) (2024)\n* [Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference](https://huggingface.co/papers/2403.09636) (2024)\n* [ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching](https://huggingface.co/papers/2403.17312) (2024)\n* [Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks](https://huggingface.co/papers/2402.04248) (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/2403.19888.json

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+{"paper_url": "https://huggingface.co/papers/2403.19888", "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* [SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series](https://huggingface.co/papers/2403.15360) (2024)\n* [LocalMamba: Visual State Space Model with Windowed Selective Scan](https://huggingface.co/papers/2403.09338) (2024)\n* [Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data](https://huggingface.co/papers/2402.05892) (2024)\n* [Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling](https://huggingface.co/papers/2402.18508) (2024)\n* [VL-Mamba: Exploring State Space Models for Multimodal Learning](https://huggingface.co/papers/2403.13600) (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/2403.19928.json

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+{"paper_url": "https://huggingface.co/papers/2403.19928", "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* [Linear Transformers with Learnable Kernel Functions are Better In-Context Models](https://huggingface.co/papers/2402.10644) (2024)\n* [DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models](https://huggingface.co/papers/2403.00818) (2024)\n* [Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling](https://huggingface.co/papers/2402.18508) (2024)\n* [Anchor-based Large Language Models](https://huggingface.co/papers/2402.07616) (2024)\n* [WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More](https://huggingface.co/papers/2402.12065) (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/2403.20041.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.20041", "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* [QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference](https://huggingface.co/papers/2402.10076) (2024)\n* [FlattenQuant: Breaking Through the Inference Compute-bound for Large Language Models with Per-tensor Quantization](https://huggingface.co/papers/2402.17985) (2024)\n* [WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More](https://huggingface.co/papers/2402.12065) (2024)\n* [ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching](https://huggingface.co/papers/2403.17312) (2024)\n* [EdgeQAT: Entropy and Distribution Guided Quantization-Aware Training for the Acceleration of Lightweight LLMs on the Edge](https://huggingface.co/papers/2402.10787) (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/2403.20275.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.20275", "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* [Touch-GS: Visual-Tactile Supervised 3D Gaussian Splatting](https://huggingface.co/papers/2403.09875) (2024)\n* [DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshing](https://huggingface.co/papers/2403.17822) (2024)\n* [2D Gaussian Splatting for Geometrically Accurate Radiance Fields](https://huggingface.co/papers/2403.17888) (2024)\n* [SplatFace: Gaussian Splat Face Reconstruction Leveraging an Optimizable Surface](https://huggingface.co/papers/2403.18784) (2024)\n* [Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting](https://huggingface.co/papers/2402.15870) (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/2403.20309.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.20309", "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* [GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting](https://huggingface.co/papers/2402.10259) (2024)\n* [BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting](https://huggingface.co/papers/2403.11831) (2024)\n* [Q-SLAM: Quadric Representations for Monocular SLAM](https://huggingface.co/papers/2403.08125) (2024)\n* [WSCLoc: Weakly-Supervised Sparse-View Camera Relocalization](https://huggingface.co/papers/2403.15272) (2024)\n* [CoherentGS: Sparse Novel View Synthesis with Coherent 3D Gaussians](https://huggingface.co/papers/2403.19495) (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/2403.20327.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.20327", "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* [Multilingual E5 Text Embeddings: A Technical Report](https://huggingface.co/papers/2402.05672) (2024)\n* [SoftQE: Learned Representations of Queries Expanded by LLMs](https://huggingface.co/papers/2402.12663) (2024)\n* [Repetition Improves Language Model Embeddings](https://huggingface.co/papers/2402.15449) (2024)\n* [Nomic Embed: Training a Reproducible Long Context Text Embedder](https://huggingface.co/papers/2402.01613) (2024)\n* [BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation](https://huggingface.co/papers/2402.03216) (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/2403.20329.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.20329", "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 Generalization in Semantic Parsing by Increasing Natural Language Variation](https://huggingface.co/papers/2402.08666) (2024)\n* [ChatEL: Entity Linking with Chatbots](https://huggingface.co/papers/2402.14858) (2024)\n* [Large Language Models as Zero-shot Dialogue State Tracker through Function Calling](https://huggingface.co/papers/2402.10466) (2024)\n* [Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification](https://huggingface.co/papers/2402.03686) (2024)\n* [A Comparative Analysis of Conversational Large Language Models in Knowledge-Based Text Generation](https://huggingface.co/papers/2402.01495) (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/2403.20331.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2403.20331", "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* [Uncertainty-Aware Evaluation for Vision-Language Models](https://huggingface.co/papers/2402.14418) (2024)\n* [MULTI: Multimodal Understanding Leaderboard with Text and Images](https://huggingface.co/papers/2402.03173) (2024)\n* [VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning](https://huggingface.co/papers/2403.13164) (2024)\n* [Multi-modal preference alignment remedies regression of visual instruction tuning on language model](https://huggingface.co/papers/2402.10884) (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`"}