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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 901–950 of 9051 papers

TitleStatusHype
Enhancing Adversarial Transferability with Checkpoints of a Single Model's Training—0
One-Way Ticket: Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models—0
Enhancing Diversity for Data-free Quantization—0
DH-Set: Improving Vision-Language Alignment with Diverse and Hybrid Set-Embeddings Learning—0
Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation—0
beta-FFT: Nonlinear Interpolation and Differentiated Training Strategies for Semi-Supervised Medical Image Segmentation—0
Improving Accuracy and Calibration via Differentiated Deep Mutual Learning—0
Illumination Spectrum Estimation for Multispectral Images via Surface Reflectance Modeling and Spatial-Spectral Feature GenerationCode0
SLVR: Super-Light Visual Reconstruction via Blueprint Controllable Convolutions and Exploring Feature Diversity RepresentationCode0
Keyframe-Guided Creative Video Inpainting—0
Data Distributional Properties As Inductive Bias for Systematic Generalization—0
Scaling up Image Segmentation across Data and Tasks—0
Unity in Diversity: Video Editing via Gradient-Latent Purification—0
DynScene: Scalable Generation of Dynamic Robotic Manipulation Scenes for Embodied AI—0
DIVE: Diversified Iterative Self-ImprovementCode0
An LLM-Empowered Adaptive Evolutionary Algorithm For Multi-Component Deep Learning Systems—0
Diffusion Prism: Enhancing Diversity and Morphology Consistency in Mask-to-Image Diffusion—0
Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement LearningCode0
RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented InstructionsCode2
Linear Precoding Design for OTFS Systems in Time/Frequency Selective Fading Channels—0
CNC: Cross-modal Normality Constraint for Unsupervised Multi-class Anomaly Detection—0
Echoes in AI: Quantifying Lack of Plot Diversity in LLM Outputs—0
A Method for Enhancing the Safety of Large Model Generation Based on Multi-dimensional Attack and Defense—0
VoxVietnam: a Large-Scale Multi-Genre Dataset for Vietnamese Speaker Recognition—0
Addressing Challenges in Data Quality and Model Generalization for Malaria Detection—0
PQD: Post-training Quantization for Efficient Diffusion Models—0
Intrinsic meaning, perception, and matching—0
A Large-Scale Study on Video Action Dataset CondensationCode1
QUBE: Enhancing Automatic Heuristic Design via Quality-Uncertainty Balanced EvolutionCode0
Exploring and Controlling Diversity in LLM-Agent Conversation—0
Toward Intelligent and Secure Cloud: Large Language Model Empowered Proactive DefenseCode1
Enhancing Annotated Bibliography Generation with LLM Ensembles—0
The Synergy of Automated Pipelines with Prompt Engineering and Generative AI in Web Crawling—0
No Preference Left Behind: Group Distributional Preference OptimizationCode1
Revealing the Shape of Genome Space via K-mer TopologyCode0
Multi-scale Latent Point Consistency Models for 3D Shape Generation—0
Diverse Rare Sample Generation with Pretrained GANsCode0
Focusing Image Generation to Mitigate Spurious Correlations—0
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task SynthesisCode3
Attribution for Enhanced Explanation with Transferable Adversarial eXploration—0
Learning states enhanced knowledge tracing: Simulating the diversity in real-world learning process—0
RecLM: Recommendation Instruction TuningCode2
UniAvatar: Taming Lifelike Audio-Driven Talking Head Generation with Comprehensive Motion and Lighting Control—0
Experimental Study of RCS Diversity with Novel No-divergent OAM Beams—0
Enhanced Recommendation Combining Collaborative Filtering and Large Language Models—0
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration PathCode1
Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning—0
Dissecting CLIP: Decomposition with a Schur Complement-based ApproachCode0
DynaGRAG | Exploring the Topology of Information for Advancing Language Understanding and Generation in Graph Retrieval-Augmented Generation—0
Survey of Pseudonymization, Abstractive Summarization & Spell Checker for Hindi and Marathi—0
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