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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 2826–2850 of 9051 papers

TitleStatusHype
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation—0
Symmetry-Breaking Augmentations for Ad Hoc Teamwork—0
Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence—0
Discovering Sensorimotor Agency in Cellular Automata using Diversity SearchCode0
Cosmic radiation drives quasi-periodic changes in the diversity of siliceous marine microplankton—0
Generating Diverse Translation with Perturbed kNN-MT—0
UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition—0
Dataset Clustering for Improved Offline Policy LearningCode0
MultiMedEval: A Benchmark and a Toolkit for Evaluating Medical Vision-Language ModelsCode2
MaxMin-RLHF: Alignment with Diverse Human Preferences—0
DUEL: Duplicate Elimination on Active Memory for Self-Supervised Class-Imbalanced Learning—0
One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill—0
Topic Modeling as Multi-Objective Contrastive Optimization—0
Understanding fitness landscapes in morpho-evolution via local optima networks—0
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model—0
Beware of Words: Evaluating the Lexical Diversity of Conversational LLMs using ChatGPT as Case Study—0
SAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic ParadigmCode0
Multi-Modal Emotion Recognition by Text, Speech and Video Using Pretrained Transformers—0
A two-stage algorithm in evolutionary product unit neural networks for classification—0
Monopoly agenda control with privately informed voters—0
Towards a Systematic Approach to Design New Ensemble Learning AlgorithmsCode0
ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies—0
Rethinking Data Selection for Supervised Fine-Tuning—0
Scrapping The Web For Early Wildfire Detection: A New Annotated Dataset of Images and Videos of Smoke Plumes In-the-wild—0
Randomness Is All You Need: Semantic Traversal of Problem-Solution Spaces with Large Language ModelsCode0
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