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

https://github.com/aiot-mlsys-lab/fedrolex

공식 코드

FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction

https://github.com/aiverification/neuralmc

공식 코드

Neural Model Checking

https://github.com/aivodji/mrce

공식 코드

Model extraction from counterfactual explanations

https://github.com/ajaech/query_completion

공식 코드

Personalized Language Model for Query Auto-Completion

https://github.com/ajbrock/SMASH

공식 코드

SMASH: One-Shot Model Architecture Search through HyperNetworks

https://github.com/aklipf/gemsnet

공식 코드

Unified Model for Crystalline Material Generation

https://github.com/akononovicius/nlin-garch-and-1f-noise

공식 코드

Nonlinear GARCH model and 1/f noise

https://github.com/akshaykr/oracle_cb

공식 코드

Model selection for contextual bandits

https://github.com/alansun17904/circuit-stability

공식 코드

Circuit Stability Characterizes Language Model Generalization

https://github.com/alexa/dial-guide

공식 코드

DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines

https://github.com/aliaksah/EMJMCMC2016

공식 코드

Flexible Bayesian Nonlinear Model Configuration

https://github.com/alibaba-damo-academy/worldvla

공식 코드

WorldVLA: Towards Autoregressive Action World Model

https://github.com/alibaba/federatedscope

공식 코드

Efficient Personalized Federated Learning via Sparse Model-Adaptation

https://github.com/alibaba/graphtranslator

공식 코드

GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks

https://github.com/alibeikmohammadi/compfedrl

공식 코드

Compressed Federated Reinforcement Learning with a Generative Model

https://github.com/alicebizeul/simvae

공식 코드

A Probabilistic Model Behind Self-Supervised Learning

https://github.com/allenai/contrastive-explanations

공식 코드

Contrastive Explanations for Model Interpretability

https://github.com/allenai/scibert

공식 코드

SciBERT: A Pretrained Language Model for Scientific Text

https://github.com/alontalmor/oLMpics

공식 코드

oLMpics -- On what Language Model Pre-training Captures

https://github.com/alpha-unito/model-agnostic-fl

공식 코드

Model-Agnostic Federated Learning

https://github.com/alphacatplus/vmambair

공식 코드

VmambaIR: Visual State Space Model for Image Restoration

https://github.com/alshedivat/cen

공식 코드

The Intriguing Properties of Model Explanations

https://github.com/alwaysfhao/tim4rec

공식 코드

TiM4Rec: An Efficient Sequential Recommendation Model Based on Time-Aware Structured State Space Duality Model

https://github.com/ama-cmfai/lambda

공식 코드

LAMBDA: A Large Model Based Data Agent

https://github.com/amarasovic/neural-abstract-anaphora

공식 코드

A Mention-Ranking Model for Abstract Anaphora Resolution

https://github.com/amazon-research/quantile-aggregation

공식 코드

Flexible Model Aggregation for Quantile Regression

https://github.com/amazon-science/LC-PLM

공식 코드

Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers

https://github.com/amballaavinash/modelselection

공식 코드

Automated Model Selection for Tabular Data

https://github.com/amberyzheng/MIMA

공식 코드

Multi-concept Model Immunization through Differentiable Model Merging

https://github.com/amberyzheng/model-immunization-cond-num

공식 코드

Model Immunization from a Condition Number Perspective

https://github.com/amirhk/mace

공식 코드

Model-Agnostic Counterfactual Explanations for Consequential Decisions

https://github.com/amurtadha/alclam

공식 코드

AlcLaM: Arabic Dialectal Language Model

https://github.com/anaymehrotra/bias-in-evaluation-processes

공식 코드

Bias in Evaluation Processes: An Optimization-Based Model

https://github.com/andersgmadsen/tcav-bendr

공식 코드

Concept-based explainability for an EEG transformer model

https://github.com/andrade-stats/robustBayesClustering

공식 코드

Robust Bayesian Model Selection for Variable Clustering with the Gaussian Graphical Model

https://github.com/andreArtelt/ContrastiveExplanationsForModelAdaptations

공식 코드

Contrastive Explanations for Explaining Model Adaptations

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