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

https://github.com/jiachenlei/rrcm

공식 코드

Robust Representation Consistency Model via Contrastive Denoising

https://github.com/jialetao/dam

공식 코드

Structure-Aware Motion Transfer with Deformable Anchor Model

https://github.com/jianfa/recipesnap-a-lightweight-image-to-recipe-model

공식 코드

RecipeSnap -- a lightweight image-to-recipe model

https://github.com/jieyilong/tree-of-thought-puzzle-solver

공식 코드

Large Language Model Guided Tree-of-Thought

https://github.com/jihaonew/uta

공식 코드

Enhancing Vision-Language Model with Unmasked Token Alignment

https://github.com/jingtaozhan/DRhard

공식 코드

Optimizing Dense Retrieval Model Training with Hard Negatives

https://github.com/jinheonbaek/kalmv

공식 코드

Knowledge-Augmented Language Model Verification

https://github.com/jinpeng01/hgn

공식 코드

Hero-Gang Neural Model For Named Entity Recognition

https://github.com/jinyiw/guideddiffusionpur

공식 코드

Guided Diffusion Model for Adversarial Purification

https://github.com/jinyjelly/videomamba

공식 코드

VideoMamba: Spatio-Temporal Selective State Space Model

https://github.com/jisacks/dmpo

공식 코드

Deep Model Predictive Optimization

https://github.com/jity16/when-to-update-your-model-constrained-model-based-reinforcement-learning

공식 코드

When to Update Your Model: Constrained Model-based Reinforcement Learning

https://github.com/jiyuanfeng/ddp

공식 코드

DDP: Diffusion Model for Dense Visual Prediction

https://github.com/jjchy/cg_score

공식 코드

Data Valuation Without Training of a Model

https://github.com/jkwang28/osdface

공식 코드

OSDFace: One-Step Diffusion Model for Face Restoration

https://github.com/jlee118/nprm

공식 코드

A Neural Pairwise Ranking Model for Readability Assessment

https://github.com/jlko/active-testing

공식 코드

Active Testing: Sample-Efficient Model Evaluation

https://github.com/joaoantoniocn/AM-MobileNet1D

공식 코드

AM-MobileNet1D: A Portable Model for Speaker Recognition

https://github.com/john-bradshaw/molecule-chef

공식 코드

A Model to Search for Synthesizable Molecules

https://github.com/john-hawkins/MinViME

공식 코드

Minimum Viable Model Estimates for Machine Learning Projects

https://github.com/john-hewitt/model-editing-canonical-examples

공식 코드

Model Editing with Canonical Examples

https://github.com/john-hewitt/truncation-sampling

공식 코드

Truncation Sampling as Language Model Desmoothing

https://github.com/jonas-maj/ensemble-adversarial-robustness

공식 코드

Certifying Joint Adversarial Robustness for Model Ensembles

https://github.com/jonas-sm/td-mpc-srl

공식 코드

Model Predictive Control with Self-supervised Representation Learning

https://github.com/jonasricker/diffusion-model-deepfake-detection

공식 코드

Towards the Detection of Diffusion Model Deepfakes

https://github.com/josecannete/spanish-corpora

공식 코드

Spanish Pre-trained BERT Model and Evaluation Data

https://github.com/josesousaribeiro/XAI-Benchmark

공식 코드

Does Dataset Complexity Matters for Model Explainers?

https://github.com/josesousaribeiro/exirt

공식 코드

Explanations Based on Item Response Theory (eXirt): A Model-Specific Method to Explain Tree-Ensemble Model in Trust Perspective

https://github.com/josesousaribeiro/exirt-xai-benchmark

공식 코드

Explanations Based on Item Response Theory (eXirt): A Model-Specific Method to Explain Tree-Ensemble Model in Trust Perspective

https://github.com/josesousaribeiro/exirt-xai-pipeline

공식 코드

Explanations Based on Item Response Theory (eXirt): A Model-Specific Method to Explain Tree-Ensemble Model in Trust Perspective

https://github.com/joshengels/multidimensionalfeatures

공식 코드

Not All Language Model Features Are Linear

https://github.com/jpain3/taming-the-bull

공식 코드

Behaviorally Grounded Model-Based and Model Free Cost Reduction in a Simulated Multi-Echelon Supply Chain

https://github.com/jpickard1/brad

공식 코드

Language Model Powered Digital Biology with BRAD

https://github.com/jspan/PHYSICS_SR

공식 코드

Image Formation Model Guided Deep Image Super-Resolution

https://github.com/juice500ml/xlm_to_xlsr

공식 코드

Distilling a Pretrained Language Model to a Multilingual ASR Model

https://github.com/juliagni/geometricmachinelearning.jl

공식 코드

Symplectic Autoencoders for Model Reduction of Hamiltonian Systems

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