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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 651–675 of 9051 papers

TitleStatusHype
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning—0
MoMa: A Modular Deep Learning Framework for Material Property Prediction—0
Reducing false positives in strong lens detection through effective augmentation and ensemble learning—0
I-MCTS: Enhancing Agentic AutoML via Introspective Monte Carlo Tree SearchCode1
Affinity and Diversity: A Unified Metric for Demonstration Selection via Internal Representations—0
Exploring Advanced Techniques for Visual Question Answering: A Comprehensive Comparison—0
An Enhancement of Jiang, Z., et al.s Compression-Based Classification Algorithm Applied to News Article Categorization—0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models—0
Mixed Signals: A Diverse Point Cloud Dataset for Heterogeneous LiDAR V2X Collaboration—0
Image compositing is all you need for data augmentation—0
A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment—0
Diversity-driven Data Selection for Language Model Tuning through Sparse Autoencoder—0
ETS: Efficient Tree Search for Inference-Time ScalingCode0
DiffSampling: Enhancing Diversity and Accuracy in Neural Text Generation—0
Cascading CMA-ES Instances for Generating Input-diverse Solution BatchesCode0
VITAL: A New Dataset for Benchmarking Pluralistic Alignment in Healthcare—0
Poster: SpiderSim: Multi-Agent Driven Theoretical Cybersecurity Simulation for Industrial DigitalizationCode0
Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming—0
Understanding and Evaluating Hallucinations in 3D Visual Language Models—0
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through OptionsCode0
Thinking Outside the (Gray) Box: A Context-Based Score for Assessing Value and Originality in Neural Text Generation—0
Diverse Topology Optimization using Modulated Neural FieldsCode1
On the Computational Tractability of the (Many) Shapley Values—0
Aligning Sentence Simplification with ESL Learner's Proficiency for Language AcquisitionCode0
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