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Diversity

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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.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/act-lab/release

공식 코드

Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation

https://bitbucket.org/dascim/acl2018_abssumm

공식 코드

Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization

https://bitbucket.org/wanyuchen/idsr

공식 코드

Improving End-to-End Sequential Recommendations with Intent-aware Diversification

https://github.com/00why00/pfcd

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Prompt-Free Conditional Diffusion for Multi-object Image Augmentation

https://github.com/0914eagle/code-diversity

공식 코드

Is Functional Correctness Enough to Evaluate Code Language Models? Exploring Diversity of Generated Codes

https://github.com/0frett/po-uncertainty-benchmarking

공식 코드

Benchmarking Large Language Model Uncertainty for Prompt Optimization

https://github.com/1170300521/DiFa

공식 코드

Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks

https://github.com/278287847/DEM

공식 코드

Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting

https://github.com/3DTopia/ThemeStation

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ThemeStation: Generating Theme-Aware 3D Assets from Few Exemplars

https://github.com/4DVLab/DexGrasp-Anything

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DexGrasp Anything: Towards Universal Robotic Dexterous Grasping with Physics Awareness

https://github.com/AGAPIA/BTreeGeneticFramework

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Automatic difficulty management and testing in games using a framework based on behavior trees and genetic algorithms

https://github.com/AI-NERC-NUPT/MEDM

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Entropy Minimization vs. Diversity Maximization for Domain Adaptation

https://github.com/AI-NERC-NUPT/PLR-OSNet

공식 코드

Learning Diverse Features with Part-Level Resolution for Person Re-Identification

https://github.com/AI-luyuan/GBANRecommendation

공식 코드

The Graph-Based Behavior-Aware Recommendation for Interactive News

https://github.com/AI-secure/Transferability-Reduced-Smooth-Ensemble

공식 코드

TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness

https://github.com/AI4SC/archi-guesser

공식 코드

ArchiGuesser -- AI Art Architecture Educational Game

https://github.com/AKuzina/BooVAE

공식 코드

BooVAE: Boosting Approach for Continual Learning of VAE

https://github.com/ARBML/Calliar

공식 코드

Calliar: An Online Handwritten Dataset for Arabic Calligraphy

https://github.com/AaronSun2000/MakeupAttack

공식 코드

MakeupAttack: Feature Space Black-box Backdoor Attack on Face Recognition via Makeup Transfer

https://github.com/Abdullah-88/Ensemble_Autoselection_SOCP

공식 코드

Autoselection of the Ensemble of Convolutional Neural Networks with Second-Order Cone Programming

https://github.com/Abusagit/Challenges-on-generating-structurally-diverse-graphs

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Challenges of Generating Structurally Diverse Graphs

https://github.com/Abuuu122/Dereflection-Any-Image

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Dereflection Any Image with Diffusion Priors and Diversified Data

https://github.com/Adam-Haile/vita-research-group

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Synthesizing Audio from Silent Video using Sequence to Sequence Modeling

https://github.com/AdamByerly/micro-pcb-analysis

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On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBs

https://github.com/Aghasemian/OptimalLinkPrediction

공식 코드

Stacking Models for Nearly Optimal Link Prediction in Complex Networks

https://github.com/AhmedImtiazPrio/magnet-polarity

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Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values

https://github.com/AhmedMagdyHendawy/MOORE

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Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts

https://github.com/AlamiMejjati/GeneratingObjectStamps

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Generating Object Stamps

https://github.com/Albert0147/AaD_SFDA

공식 코드

Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation

https://github.com/AlbertoBarbado/unsupervised-outlier-transparency

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Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM

https://github.com/AlexTheBad/AP-10K

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AP-10K: A Benchmark for Animal Pose Estimation in the Wild

https://github.com/Alibaba-MIIL/ZS_SDL

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Semantic Diversity Learning for Zero-Shot Multi-label Classification

https://github.com/Alibaba-NLP/CoFE-RAG

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CoFE-RAG: A Comprehensive Full-chain Evaluation Framework for Retrieval-Augmented Generation with Enhanced Data Diversity

https://github.com/Alibaba-NLP/EcomGPT

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EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce

https://github.com/AngeLouCN/SAM-2_Surgical_Video

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Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2

https://github.com/AnnikaLindh/Diverse_and_Specific_Image_Captioning

공식 코드

Generating Diverse and Meaningful Captions

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.