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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 2751–2800 of 9051 papers

TitleStatusHype
Social Intelligence Data Infrastructure: Structuring the Present and Navigating the Future—0
RORA: Robust Free-Text Rationale EvaluationCode0
TroubleLLM: Align to Red Team Expert—0
Priority Sampling of Large Language Models for Compilers—0
OccTransformer: Improving BEVFormer for 3D camera-only occupancy prediction—0
Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality EstimationCode2
Improving Open-Ended Text Generation via Adaptive DecodingCode1
Multi-FAct: Assessing Factuality of Multilingual LLMs using FActScoreCode0
Autoencoder-based General Purpose Representation Learning for Customer Embedding—0
Ensemble Methodology:Innovations in Credit Default Prediction Using LightGBM, XGBoost, and LocalEnsemble—0
Image-Text Matching with Multi-View Attention—0
SoFA: Shielded On-the-fly Alignment via Priority Rule FollowingCode0
Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning—0
MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-TuningCode1
Federated Learning for Estimating Heterogeneous Treatment Effects—0
DivAvatar: Diverse 3D Avatar Generation with a Single Prompt—0
RISAR: RIS-assisted Human Activity Recognition with Commercial Wi-Fi Devices—0
RECOST: External Knowledge Guided Data-efficient Instruction Tuning—0
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward EncodingsCode2
Mitigating Distributional Shift in Semantic Segmentation via Uncertainty Estimation from Unlabelled Data—0
TrustMol: Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics—0
DiffuCOMET: Contextual Commonsense Knowledge DiffusionCode0
Against Filter Bubbles: Diversified Music Recommendation via Weighted Hypergraph Embedding Learning—0
Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower ResolutionsCode1
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts—0
On Languaging a Simulation Engine—0
Topic-to-essay generation with knowledge-based content selection—0
Finding Near-Optimal Portfolios With Quality-Diversity—0
ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion ModelingCode0
Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities—0
NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated DataCode1
CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models—0
Hands-Free VR—0
Fine-Grained Detoxification via Instance-Level Prefixes for Large Language ModelsCode0
Ten computational challenges in human virome studies—0
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control—0
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization—0
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns—0
Mirror: A Multiple-perspective Self-Reflection Method for Knowledge-rich ReasoningCode1
Swin3D++: Effective Multi-Source Pretraining for 3D Indoor Scene UnderstandingCode3
Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting—0
MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation SystemsCode1
Visual Hallucinations of Multi-modal Large Language ModelsCode1
Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetCode2
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization—0
LongWanjuan: Towards Systematic Measurement for Long Text QualityCode1
Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness—0
Diversity-Aware k-Maximum Inner Product Search Revisited—0
Se^2: Sequential Example Selection for In-Context Learning—0
DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual LearningCode1
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