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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 6151–6175 of 9051 papers

TitleStatusHype
On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference—0
Artefact Retrieval: Overview of NLP Models with Knowledge Base Access—0
On the clustering of correlated random variables—0
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach—0
On the Complexity of Optimising Variants of Phylogenetic Diversity on Phylogenetic Networks—0
On the Computational Tractability of the (Many) Shapley Values—0
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization—0
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness—0
On the Diversity and Coded Modulation Design of Fluid Antenna Systems—0
On the Diversity and Limits of Human Explanations—0
On the Diversity and Limits of Human Explanations—0
ArtCrafter: Text-Image Aligning Style Transfer via Embedding Reframing—0
Uncertainty Sentence Sampling by Virtual Adversarial Perturbation—0
On the Diversity of Synthetic Data and its Impact on Training Large Language Models—0
On the Dynamics of Mating Preferences in Genetic Programming—0
On the Effectiveness of Acoustic BPE in Decoder-Only TTS—0
On the Effectiveness of Genetic Operations in Symbolic Regression—0
Array-Informed Waveform Design for Active Sensing: Diversity, Redundancy, and Identifiability—0
UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations—0
A Robust Contrastive Alignment Method For Multi-Domain Text Classification—0
Unconditional Diffusion Guidance—0
On the Ethical Limits of Natural Language Processing on Legal Text—0
Achieving Distributed MIMO Performance with Repeater-Assisted Cellular Massive MIMO—0
On the Evaluation of Generative Robotic Simulations—0
On the Fairness, Diversity and Reliability of Text-to-Image Generative Models—0
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