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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

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Showing 4051–4075 of 9051 papers

TitleStatusHype
How to Ask Good Questions? Try to Leverage Paraphrases—0
GFlowNet Fine-tuning for Diverse Correct Solutions in Mathematical Reasoning Tasks—0
GFlowVLM: Enhancing Multi-step Reasoning in Vision-Language Models with Generative Flow Networks—0
HybridLinker: Topology-Guided Posterior Sampling for Enhanced Diversity and Validity in 3D Molecular Linker Generation—0
Image Processing in Floriculture Using a robotic Mobile Platform—0
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network—0
GI-Free Pilot-Aided Channel Estimation for Affine Frequency Division Multiplexing Systems—0
GigaHands: A Massive Annotated Dataset of Bimanual Hand Activities—0
Gini Coefficient as a Unified Metric for Evaluating Many-versus-Many Similarity in Vector Spaces—0
giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI—0
Improving Intelligence of Evolutionary Algorithms Using Experience Share and Replay—0
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization—0
Diverse Ensemble Evolution: Curriculum Data-Model Marriage—0
DiverseDream: Diverse Text-to-3D Synthesis with Augmented Text Embedding—0
Blessing of Class Diversity in Pre-training—0
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP—0
D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning—0
The loss landscape of deep linear neural networks: a second-order analysis—0
Auto-Ensemble: An Adaptive Learning Rate Scheduling based Deep Learning Model Ensembling—0
Global-scale phylogenetic linguistic inference from lexical resources—0
Diverse Diffusion: Enhancing Image Diversity in Text-to-Image Generation—0
Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods—0
Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping—0
D4: Text-guided diffusion model-based domain adaptive data augmentation for vineyard shoot detection—0
A new selection strategy for selective cluster ensemble based on Diversity and Independency—0
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