Papers with Code 아카이브
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://github.com/alpv95/Dank-Learning
https://github.com/alrope123/prompt-waywardness
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
https://github.com/altsoph/paranoid_transformer
https://github.com/amazon-research/auto-cot
Automatic Chain of Thought Prompting in Large Language Models
https://github.com/amazon-science/chronos-forecasting
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/amazon-science/llm-asymptotic-decoding
REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic Entropy
https://github.com/amazon-science/tabsyn
https://github.com/amidos2006/Mario-AI-Framework
https://github.com/amiyamandal-dev/pegasus
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies
https://github.com/amogh7joshi/media-vision
https://github.com/amolk/editsql
https://github.com/amoretti86/PSVO
https://github.com/anbunathan/WikiHow-Semantic
https://github.com/andrearama/Deep-Auxiliary-Classifier-GAN
https://github.com/andreas128/NTIRE21_Learning_SR_Space
SRFlow: Learning the Super-Resolution Space with Normalizing Flow
https://github.com/andrei-rizoiu/CommentWatcher
CommentWatcher: An Open Source Web-based platform for analyzing discussions on web forums
https://github.com/andrewliao11/unrolled-gans
https://github.com/andy194673/nlg-scvae
Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems
https://github.com/anitadala/SkinLesionAnalyzer
https://github.com/ankita1404/ConversationalChatBot
A Diversity-Promoting Objective Function for Neural Conversation Models
https://github.com/anthonysicilia/change-that-matters-acl2022
LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue
https://github.com/anthonysicilia/pacbayes-adaptation-uai2022
LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue
https://github.com/apaszke/pytorch-dist
https://github.com/apple2373/PyTorch-SmallGAN
Image Generation From Small Datasets via Batch Statistics Adaptation
https://github.com/apratimbhattacharyya18/seg_pred
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods
https://github.com/araffin/srl-zoo
S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning
https://github.com/aricsvenz/AI_for_Drugs
ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?
https://github.com/ariesiitr/Image-Colourization
https://github.com/armaanjawed/Skin-Cancer-Web_App
https://github.com/artcg/BEGAN
https://github.com/artessay/sama
https://github.com/aryasbandopadhyay/Chatbot-rnn
A Diversity-Promoting Objective Function for Neural Conversation Models
https://github.com/asahi417/lm-question-generation
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/asahi417/lmppl
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/ashen-sensored/sd_webui_SAG
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.