https://github.com/Jiaju-Chen/UpliftRec
공식 코드Treatment Effect Estimation for User Interest Exploration on Recommender Systems
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/Jihuai-wpy/MetaAlign
공식 코드MetaAlign: Align Large Language Models with Diverse Preferences during Inference Time
https://github.com/Jingtong0527/DRI-IQA
공식 코드Dual-Representation Interaction Driven Image Quality Assessment with Restoration Assistance
https://github.com/JinshanZeng/StrokeGAN
공식 코드StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding
https://github.com/Jinx630/Pseudo-Visual-Prompt
공식 코드TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt
https://github.com/Jiuzhouh/Multi-Score
공식 코드https://github.com/JiwanChung/long-story-short
공식 코드Long Story Short: a Summarize-then-Search Method for Long Video Question Answering
https://github.com/JoHof/lungmask
공식 코드https://github.com/JocelynSong/IsEM-Pro
공식 코드Importance Weighted Expectation-Maximization for Protein Sequence Design
https://github.com/Johann-Huber/qd_grasp
공식 코드Quality Diversity under Sparse Reward and Sparse Interaction: Application to Grasping in Robotics
https://github.com/JonathanPrexl/SenPa-MAE
공식 코드SenPa-MAE: Sensor Parameter Aware Masked Autoencoder for Multi-Satellite Self-Supervised Pretraining
https://github.com/JordanAsh/badge
공식 코드Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
https://github.com/JumpyPizza/align-sentence-simplification-with-ESL-learner
공식 코드Aligning Sentence Simplification with ESL Learner's Proficiency for Language Acquisition
https://github.com/JupitersMight/DI2
공식 코드DI2: prior-free and multi-item discretization ofbiomedical data and its applications
https://github.com/JuseonDo/DL-MMR
공식 코드Considering Length Diversity in Retrieval-Augmented Summarization
https://github.com/Juyong/CaricatureFace
공식 코드Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model
https://github.com/Juyong/FacePSNet
공식 코드https://github.com/KDongYoung/Calibration-Free-Driver-Drowsiness-Classification-based-on-Manifold-Level-Augmentation
공식 코드Calibration-Free Driver Drowsiness Classification based on Manifold-Level Augmentation
https://github.com/KID-7391/seeking-the-shape-of-sound
공식 코드Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association
https://github.com/KU-CVLAB/DAG
공식 코드DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models
https://github.com/KU-CVLAB/RetDream
공식 코드Retrieval-Augmented Score Distillation for Text-to-3D Generation
https://github.com/KU-CVLAB/Self-Attention-Guidance
공식 코드Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
https://github.com/KaiDMML/FakeNewsNet
공식 코드https://github.com/KaiyangZhou/Dassl.pytorch
공식 코드https://github.com/KaiyangZhou/mixstyle-release
공식 코드https://github.com/KaiyangZhou/vsumm-reinforce
공식 코드https://github.com/KazutoshiShinoda/VQAG
공식 코드https://github.com/KennthShang/PhaGCN
공식 코드Bacteriophage classification for assembled contigs using Graph Convolutional Network
https://github.com/Kenyaggel/MLoRA
공식 코드MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
https://github.com/KevinCortacero/Kartezio
공식 코드Kartezio: Evolutionary Design of Explainable Pipelines for Biomedical Image Analysis
https://github.com/KevinKecc/SRN
공식 코드SRN: Side-output Residual Network for Object Symmetry Detection in the Wild
https://github.com/Khrylx/DLow
공식 코드DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
https://github.com/KimYenny/HeterogeneousRF
공식 코드https://github.com/KomeijiForce/KeyNavi
공식 코드Correlation and Navigation in the Vocabulary Key Representation Space of Language Models
https://github.com/KumapowerLIU/PD-GAN
공식 코드https://github.com/Kyubyong/quasi-rnn
공식 코드Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss German
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.