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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/slab-nlp/multimodal_clustering
공식 코드A Computational Acquisition Model for Multimodal Word Categorization
https://github.com/slds-lmu/mbt_comparison
공식 코드Leveraging Model-based Trees as Interpretable Surrogate Models for Model Distillation
https://github.com/slientge/sequential_recommendation_tensorflow
공식 코드Sequential Recommendation Model for Next Purchase Prediction
https://github.com/slit-ai/fusechat-3.0
공식 코드FuseChat-3.0: Preference Optimization Meets Heterogeneous Model Fusion
https://github.com/slp-rl/salmon
공식 코드https://github.com/smithjoshua001/ARDL
공식 코드https://github.com/smsharma/awesome-neural-sbi
공식 코드https://github.com/snap-research/SF-V
공식 코드https://github.com/snoels/fingeit
공식 코드https://github.com/snowflakedb/arcticinference
공식 코드SuffixDecoding: Extreme Speculative Decoding for Emerging AI Applications
https://github.com/snu-mllab/context-memory
공식 코드Compressed Context Memory For Online Language Model Interaction
https://github.com/snudatalab/GraphAug
공식 코드Model-Agnostic Augmentation for Accurate Graph Classification
https://github.com/so-cool/crossmodelfairness
공식 코드Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity
https://github.com/so-cool/individualfairness
공식 코드Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity
https://github.com/socialfoundations/backward_baselines
공식 코드https://github.com/sohanseth/mcls
공식 코드https://github.com/somuchtome/faceswap
공식 코드https://github.com/sony/hi-resldm
공식 코드High-Resolution Speech Restoration with Latent Diffusion Model
https://github.com/sonyai/ratp
공식 코드https://github.com/soply/local_sim_experiments
공식 코드https://github.com/sotetsuk/alpha-dimt-icmlws
공식 코드Neural Sequence Model Training via $α$-divergence Minimization
https://github.com/sphinxteam/StructuredPrior_demo
공식 코드https://github.com/spitis/mocoda
공식 코드https://github.com/sprintml/finetuning_var_dp
공식 코드https://github.com/srishtigautam/protovae
공식 코드ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
https://github.com/ssethz/mcbo
공식 코드https://github.com/ssg-research/falseclaims
공식 코드https://github.com/stanford-crfm/fmti
공식 코드https://github.com/stanford-crfm/halie
공식 코드https://github.com/stanfordasl/rompc
공식 코드https://github.com/stanfordhci/modelsketchbook
공식 코드Model Sketching: Centering Concepts in Early-Stage Machine Learning Model Design
https://github.com/steerapi/daimon
공식 코드DaiMoN: A Decentralized Artificial Intelligence Model Network
https://github.com/stefanospert/equivariant_optimization_cr
공식 코드Improving Equivariant Model Training via Constraint Relaxation
https://github.com/stefanradev93/BayesFlow
공식 코드Amortized Bayesian model comparison with evidential deep learning
https://github.com/stilllu/asiv
공식 코드Asymmetric feature interaction for interpreting model predictions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.