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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 176200 of 9051 papers

TitleStatusHype
Multi-Space Alignments Towards Universal LiDAR SegmentationCode2
IndicGenBench: A Multilingual Benchmark to Evaluate Generation Capabilities of LLMs on Indic LanguagesCode2
The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language ModelsCode2
MAexp: A Generic Platform for RL-based Multi-Agent ExplorationCode2
Token-level Direct Preference OptimizationCode2
VBR: A Vision Benchmark in RomeCode2
in2IN: Leveraging individual Information to Generate Human INteractionsCode2
OmniSat: Self-Supervised Modality Fusion for Earth ObservationCode2
Bridging Remote Sensors with Multisensor Geospatial Foundation ModelsCode2
Guide to k-mer approaches for genomics across the tree of lifeCode2
LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented DiffusionCode2
Protein Conformation Generation via Force-Guided SE(3) Diffusion ModelsCode2
MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space ModelsCode2
Face2Diffusion for Fast and Editable Face PersonalizationCode2
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-TrainingCode2
UniCtrl: Improving the Spatiotemporal Consistency of Text-to-Video Diffusion Models via Training-Free Unified Attention ControlCode2
TempCompass: Do Video LLMs Really Understand Videos?Code2
WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image SynthesisCode2
Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality EstimationCode2
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward EncodingsCode2
Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetCode2
Geometry-Informed Neural NetworksCode2
MultiMedEval: A Benchmark and a Toolkit for Evaluating Medical Vision-Language ModelsCode2
SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language ModelsCode2
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based PoliciesCode2
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