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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 1726–1750 of 9051 papers

TitleStatusHype
Causal-Guided Active Learning for Debiasing Large Language ModelsCode1
HiFAKES: High-frequency synthetic appliance signatures generator for non-intrusive load monitoring—0
Multi-Task Curriculum Graph Contrastive Learning with Clustering Entropy Guidance—0
Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuation—0
SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging—0
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender SystemsCode0
Transformers are Minimax Optimal Nonparametric In-Context Learners—0
MakeupAttack: Feature Space Black-box Backdoor Attack on Face Recognition via Makeup TransferCode0
CARLA Drone: Monocular 3D Object Detection from a Different Perspective—0
SynPlay: Importing Real-world Diversity for a Synthetic Human Dataset—0
Interpretable Long-term Action Quality AssessmentCode1
LAHAJA: A Robust Multi-accent Benchmark for Evaluating Hindi ASR SystemsCode0
Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning—0
Lookism: The overlooked bias in computer vision—0
Mechanics promotes coherence in heterogeneous active media—0
Compress Guidance in Conditional Diffusion Sampling—0
SenPa-MAE: Sensor Parameter Aware Masked Autoencoder for Multi-Satellite Self-Supervised PretrainingCode1
Ferret: Faster and Effective Automated Red Teaming with Reward-Based Scoring TechniqueCode1
DELIA: Diversity-Enhanced Learning for Instruction Adaptation in Large Language Models—0
Diversity and stylization of the contemporary user-generated visual arts in the complexity-entropy plane—0
MAPLE: Enhancing Review Generation with Multi-Aspect Prompt LEarning in Explainable Recommendation—0
GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity Prompts—0
CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language ModelsCode1
Debiased Contrastive Representation Learning for Mitigating Dual Biases in Recommender Systems—0
Threshold Filtering Packing for Supervised Fine-Tuning: Training Related Samples within Packs—0
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