https://github.com/asif-hanif/vafa
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
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/asprenger/keras_acgan
https://github.com/assulthoni/TweetSentimentIndoBERT
IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding
https://github.com/aswinapk/chatbot_rnn
A Diversity-Promoting Objective Function for Neural Conversation Models
https://github.com/atreyasha/semantic-isometry-nmt
https://github.com/audio-captioning/clotho-dataset
https://github.com/aulrichsen/sronn
Self-Organized Operational Neural Networks with Generative Neurons
https://github.com/avyavkumar/few-shot-learning-notebooks
Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks
https://github.com/awslabs/speech-representations
DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector Quantization
https://github.com/axondeepseg/AxonDeepSynth
Unsupervised Medical Image Translation with Adversarial Diffusion Models
https://github.com/azraelzhor/tf2-VAEAC
https://github.com/baai-dcai/bunny
https://github.com/balbasty/super-resolution
https://github.com/baldassarreFe/deep-koalarization
https://github.com/bayer-science-for-a-better-life/data2text-bioleaflets
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/bazenkov/MultiCPG
Discrete Modeling of Multi-Transmitter Neural Networks with Neuron Competition
https://github.com/bbartoldson/TBA
https://github.com/bbzhu-jy16/DomainStudio
https://github.com/bbzhu-jy16/MaskDis
https://github.com/bcmi/F2GAN-Few-Shot-Image-Generation
https://github.com/bcmi/TopNet-Object-Placement
https://github.com/bdecost/pixelnet
PixelNet: Representation of the pixels, by the pixels, and for the pixels
https://github.com/bearblog/CoreRank
https://github.com/bebr2/lekube
STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionals
https://github.com/behavioral-ds/CommentWatcher
CommentWatcher: An Open Source Web-based platform for analyzing discussions on web forums
https://github.com/beierzhu/xerm
Long-tailed Recognition by Routing Diverse Distribution-Aware Experts
https://github.com/benearnthof/fm_boosting
https://github.com/bengittelson/sow-reap-paraphrasing
Neural Syntactic Preordering for Controlled Paraphrase Generation
https://github.com/bepoetree/mttod
Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context
https://github.com/bharat3012/Fake_Faces_DCGAN_GDPP_LOSS
GDPP: Learning Diverse Generations Using Determinantal Point Process
https://github.com/bhargavajs07/Packed-Wasserstein-GAN-with-GradientPenalty-Example
PacGAN: The power of two samples in generative adversarial networks
https://github.com/bhargavajs07/Packed_WGAN_GP_Example
PacGAN: The power of two samples in generative adversarial networks
https://github.com/bigscience-workshop/architecture-objective
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/billchan226/poar-srl-4-robot
S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning
https://github.com/bluejurand/Photos-colorization
https://github.com/bondarchukb/PEGASUS
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.