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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 1701–1725 of 9051 papers

TitleStatusHype
Facts are Harder Than Opinions -- A Multilingual, Comparative Analysis of LLM-Based Fact-Checking Reliability—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
Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs—0
Generating Diverse Challenging Terrains for Legged Robots Using Quality-Diversity Algorithm—0
Bregman Centroid Guided Cross-Entropy Method—0
An Empirical Study of Group Conformity in Multi-Agent Systems—0
Trajectory First: A Curriculum for Discovering Diverse Policies—0
Cross-Lingual Transfer of Cultural Knowledge: An Asymmetric Phenomenon—0
Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know?—0
Quantifying and Reducing Speaker Heterogeneity within the Common Voice Corpus for Phonetic Analysis—0
BASIL: Best-Action Symbolic Interpretable Learning for Evolving Compact RL Policies—0
The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It—0
TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data SynthesisCode0
A Reward-driven Automated Webshell Malicious-code Generator for Red-teaming—0
HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America—0
D2AF: A Dual-Driven Annotation and Filtering Framework for Visual Grounding—0
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual CompensationCode0
Reading Recognition in the Wild—0
From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning—0
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration—0
A note on the Diversity Owen values—0
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures—0
From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual MatchingCode0
Rehearsal with Auxiliary-Informed Sampling for Audio Deepfake DetectionCode0
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