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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 5001–5050 of 9051 papers

TitleStatusHype
Resource and data efficient self supervised learning—0
Resource-Constrained Edge AI with Early Exit Prediction—0
Resource Mention Extraction for MOOC Discussion Forums—0
Resources for Multilingual Hate Speech Detection—0
Response of Different Tomato Accessions to Biotic and Abiotic Stresses—0
Restricting Greed in Training of Generative Adversarial Network—0
Rethinking Diversity in Deep Neural Network Testing—0
Rethinking and Refining the Distinct Metric—0
Rethinking Data Selection for Supervised Fine-Tuning—0
Rethinking Ecological Measures Of Functional Diversity—0
Rethinking Image Cropping: Exploring Diverse Compositions From Global Views—0
Rethinking LLM-Based Recommendations: A Query Generation-Based, Training-Free Approach—0
Rethinking Parameter Counting: Effective Dimensionality Revisited—0
Rethinking Prototypical Contrastive Learning through Alignment, Uniformity and Correlation—0
RETHINKING SELF-DRIVING : MULTI -TASK KNOWLEDGE FOR BETTER GENERALIZATION AND ACCIDENT EXPLANATION ABILITY—0
Rethinking the Evaluation of Unbiased Scene Graph Generation—0
Rethinking Video Salient Object Ranking—0
Retinal Vessel Segmentation via Neuron Programming—0
Retinotopy Inspired Brain Encoding Model and the All-for-One Training Recipe—0
Retrievability in an Integrated Retrieval System: An Extended Study—0
Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies—0
Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies—0
Retrieval & Fine-Tuning for In-Context Tabular Models—0
Retrieval-guided Counterfactual Generation for QA—0
Retrieval-guided Counterfactual Generation for QA—0
Retrieval-guided Cross-view Image Synthesis—0
RetriBooru: Leakage-Free Retrieval of Conditions from Reference Images for Subject-Driven Generation—0
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison—0
Retrieving Implicit and Explicit Emotional Events Using Large Language Models—0
Revealing the Hidden Patterns: A Comparative Study on Profiling Subpopulations of MOOC Students—0
ReverseORC: Reverse Engineering of Resizable User Interface Layouts with OR-Constraints—0
Review of Clustering-Based Recommender Systems—0
Review of research on fireworks algorithm—0
Review on the Existing Language Resources for Languages of France—0
Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness—0
Revisiting Self-Consistency from Dynamic Distributional Alignment Perspective on Answer Aggregation—0
Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning—0
Revisiting the Domain Shift and Sample Uncertainty in Multi-source Active Domain Transfer—0
Revolutionising Bacterial Genomics: Graph-Based Strategies for Improved Variant Identification—0
Revolutionizing Single Cell Analysis: The Power of Large Language Models for Cell Type Annotation—0
Rigorous Evaluation of Predictive Toxicity Models by Multi-Objective Optimization of Reference Compound Lists Using Genetic Algorithms—0
Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax—0
Ring Migration Topology Helps Bypassing Local Optima—0
RIS-Aided Dual-Polarized MIMO: How Large a Surface is Needed to Beat Single Polarization?—0
RISAR: RIS-assisted Human Activity Recognition with Commercial Wi-Fi Devices—0
RIS-Assisted D2D Communication in the Presence of Interference: Outage Performance Analysis and DNN-Based Prediction—0
RIS-Assisted High Resolution Radar Sensing—0
RITA: Boost Driving Simulators with Realistic Interactive Traffic Flow—0
r/K selection of GC content in prokaryotes—0
RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learning—0
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