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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 101–150 of 9051 papers

TitleStatusHype
Combating Misinformation in the Arab World: Challenges & Opportunities—0
AutoQD: Automatic Discovery of Diverse Behaviors with Quality-Diversity Optimization—0
Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning—0
Can Foundation Models Generalise the Presentation Attack Detection Capabilities on ID Cards?—0
DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models—0
Kernel k-Medoids as General Vector Quantization—0
PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation—0
SPARTA ALIGNMENT: Collectively Aligning Multiple Language Models through Combat—0
Counterfactual reasoning: an analysis of in-context emergenceCode0
Line of Sight: On Linear Representations in VLLMs—0
Light and 3D: a methodological exploration of digitisation techniques adapted to a selection of objects from the Musée d'Archéologie Nationale—0
Subjective Perspectives within Learned Representations Predict High-Impact Innovation—0
Generalized Lotka-Volterra systems with quenched random interactions and saturating functional response—0
The Determinants of Net Interest Margin in the Turkish Banking Sector: Does Bank Ownership Matter?—0
Multiscale guidance of AlphaFold3 with heterogeneous cryo-EM data—0
Softlog-Softmax Layers and Divergences Contribute to a Computationally Dependable Ensemble Learning—0
Effects of Speaker Count, Duration, and Accent Diversity on Zero-Shot Accent Robustness in Low-Resource ASR—0
A Novel Data Augmentation Approach for Automatic Speaking Assessment on Opinion Expressions—0
Facts are Harder Than Opinions -- A Multilingual, Comparative Analysis of LLM-Based Fact-Checking Reliability—0
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid MotionsCode1
Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs—0
GAdaBoost: An Efficient and Robust AdaBoost Algorithm Based on Granular-Ball Structure—0
On the Performance of Pinching-Antenna Systems (PASS) with Orthogonal and Non-Orthogonal Multiple Access—0
Cross-Lingual Transfer of Cultural Knowledge: An Asymmetric Phenomenon—0
Generating Diverse Challenging Terrains for Legged Robots Using Quality-Diversity Algorithm—0
Trajectory First: A Curriculum for Discovering Diverse Policies—0
An Empirical Study of Group Conformity in Multi-Agent Systems—0
Bregman Centroid Guided Cross-Entropy Method—0
AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-TuningCode5
Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know?—0
BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies—0
Quantifying and Reducing Speaker Heterogeneity within the Common Voice Corpus for Phonetic Analysis—0
A note on the Diversity Owen values—0
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures—0
D2AF: A Dual-Driven Annotation and Filtering Framework for Visual Grounding—0
From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning—0
TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data SynthesisCode0
Rehearsal with Auxiliary-Informed Sampling for Audio Deepfake DetectionCode0
A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming—0
Reading Recognition in the Wild—0
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration—0
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual CompensationCode0
HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America—0
The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It—0
When Harry Meets Superman: The Role of The Interlocutor in Persona-Based Dialogue Generation—0
From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual MatchingCode0
Diversity of Transformer Layers: One Aspect of Parameter Scaling Laws—0
Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation—0
Generating Diverse Training Samples for Relation Extraction with Large Language Models—0
DiCoFlex: Model-agnostic diverse counterfactuals with flexible control—0
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