SOTAVerified

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

Showing 61516200 of 9051 papers

TitleStatusHype
On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference0
Artefact Retrieval: Overview of NLP Models with Knowledge Base Access0
On the clustering of correlated random variables0
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach0
On the Complexity of Optimising Variants of Phylogenetic Diversity on Phylogenetic Networks0
On the Computational Tractability of the (Many) Shapley Values0
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization0
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness0
On the Diversity and Coded Modulation Design of Fluid Antenna Systems0
On the Diversity and Limits of Human Explanations0
On the Diversity and Limits of Human Explanations0
ArtCrafter: Text-Image Aligning Style Transfer via Embedding Reframing0
Uncertainty Sentence Sampling by Virtual Adversarial Perturbation0
On the Diversity of Synthetic Data and its Impact on Training Large Language Models0
On the Dynamics of Mating Preferences in Genetic Programming0
On the Effectiveness of Acoustic BPE in Decoder-Only TTS0
On the Effectiveness of Genetic Operations in Symbolic Regression0
Array-Informed Waveform Design for Active Sensing: Diversity, Redundancy, and Identifiability0
UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations0
A Robust Contrastive Alignment Method For Multi-Domain Text Classification0
Unconditional Diffusion Guidance0
On the Ethical Limits of Natural Language Processing on Legal Text0
Achieving Distributed MIMO Performance with Repeater-Assisted Cellular Massive MIMO0
On the Evaluation of Generative Robotic Simulations0
On the Fairness, Diversity and Reliability of Text-to-Image Generative Models0
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer0
On-the-Fly Feature Based Rapid Speaker Adaptation for Dysarthric and Elderly Speech Recognition0
On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization0
On the Generation of Medical Question-Answer Pairs0
On the ideas of the origin of eukaryotes: a critical review0
On the Impact of Cross-Domain Data on German Language Models0
Uncovering Semantics and Topics Utilized by Threat Actors to Deliver Malicious Attachments and URLs0
On the Importance of Data Size in Probing Fine-tuned Models0
Fast uncovering of protein sequence diversity from structure0
On the Importance of Diversity in Question Generation for QA0
On the Importance of Diversity in Re-Sampling for Imbalanced Data and Rare Events in Mortality Risk Models0
On The Ingredients of an Effective Zero-shot Semantic Parser0
On the Limitations of Model Stealing with Uncertainty Quantification Models0
On the Linear Ordering Problem and the Rankability of Data0
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off0
On the Modeling Capabilities of Large Language Models for Sequential Decision Making0
On the number of equilibria of the replicator-mutator dynamics for noisy social dilemmas0
On the Performance of Non-Orthogonal Multiple Access Systems with Imperfect Successive Interference Cancellation0
On the Performance of Pinching-Antenna Systems (PASS) with Orthogonal and Non-Orthogonal Multiple Access0
On the Performance of UAV Relaying with Reconfigurable Antenna and Media Based Modulation in the Presence of Shadowed Fading0
On the potential for open-endedness in neural networks0
On the Power of Decision Trees in Auto-Regressive Language Modeling0
On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation0
On the Robustness of Active Learning0
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity0
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