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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

Showing 2650 of 9051 papers

TitleStatusHype
AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-TuningCode5
VoxBlink2: A 100K+ Speaker Recognition Corpus and the Open-Set Speaker-Identification BenchmarkCode5
ConsistentID: Portrait Generation with Multimodal Fine-Grained Identity PreservingCode5
Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent ExplorationCode4
A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQLCode4
GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from ImagesCode4
GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single ImageCode4
GaussianFormer: Scene as Gaussians for Vision-Based 3D Semantic Occupancy PredictionCode4
ActionStudio: A Lightweight Framework for Data and Training of Large Action ModelsCode4
SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory SynthesisCode4
Quality-aware Masked Diffusion Transformer for Enhanced Music GenerationCode4
Efficient Part-level 3D Object Generation via Dual Volume PackingCode4
Expressive Whole-Body 3D Gaussian AvatarCode4
AlphaFold Meets Flow Matching for Generating Protein EnsemblesCode4
A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANsCode4
Enhancing Chat Language Models by Scaling High-quality Instructional ConversationsCode4
3D Scene Generation: A SurveyCode4
Distill Any Depth: Distillation Creates a Stronger Monocular Depth EstimatorCode4
Improving Text Embeddings with Large Language ModelsCode3
INTERS: Unlocking the Power of Large Language Models in Search with Instruction TuningCode3
LongAlign: A Recipe for Long Context Alignment of Large Language ModelsCode3
Improved motif-scaffolding with SE(3) flow matchingCode3
Hierarchical Text-Conditional Image Generation with CLIP LatentsCode3
Improving Model Evaluation using SMART Filtering of Benchmark DatasetsCode3
GenWarp: Single Image to Novel Views with Semantic-Preserving Generative WarpingCode3
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