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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 3976–4000 of 9051 papers

TitleStatusHype
gRNAde: Geometric Deep Learning for 3D RNA inverse designCode2
CodeInstruct: Empowering Language Models to Edit CodeCode1
ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability AssessmentCode1
Curse of "Low" Dimensionality in Recommender Systems—0
Towards Graph-hop Retrieval and Reasoning in Complex Question Answering over Textual Database—0
GUARD: A Safe Reinforcement Learning BenchmarkCode1
A Critical Reexamination of Intra-List Distance and Dispersion—0
GrACE: Generation using Associated Code Edits—0
When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLPCode0
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning—0
NeuralMatrix: Compute the Entire Neural Networks with Linear Matrix Operations for Efficient Inference—0
Active Learning Principles for In-Context Learning with Large Language Models—0
Co-Learning Empirical Games and World Models—0
Enhancing Chat Language Models by Scaling High-quality Instructional ConversationsCode4
Sensing Diversity and Sparsity Models for Event Generation and Video Reconstruction from EventsCode0
A study of conceptual language similarity: comparison and evaluation—0
On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows—0
LMGQS: A Large-scale Dataset for Query-focused Summarization—0
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist ExaminationCode0
Progressive Sub-Graph Clustering Algorithm for Semi-Supervised Domain Adaptation Speaker Verification—0
ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model RobustnessCode0
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning ArchitectureCode0
Single Domain Dynamic Generalization for Iris Presentation Attack Detection—0
Vector Autoregressive Evolution for Dynamic Multi-Objective Optimisation—0
Diversity and Inclusion in Artificial Intelligence—0
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