Papers with Code 아카이브

model

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/Zhenzi-Weng/LaSC-ST

공식 코드

Large Model Empowered Streaming Speech Semantic Communications

https://github.com/ZilongBai/KDD2020BMGUFS

공식 코드

Block Model Guided Unsupervised Feature Selection

https://github.com/a-m-team/a-m-models

공식 코드

Leveraging Reasoning Model Answers to Enhance Non-Reasoning Model Capability

https://github.com/a2502503/echoone

공식 코드

EchoONE: Segmenting Multiple echocardiography Planes in One Model

https://github.com/aalmodovares/decaflow

공식 코드

DeCaFlow: A Deconfounding Causal Generative Model

https://github.com/abc03570128/jailbreaking-attack-against-multimodal-large-language-model

공식 코드

Jailbreaking Attack against Multimodal Large Language Model

https://github.com/abrochar/pp_syn

공식 코드

Particle gradient descent model for point process generation

https://github.com/acmi-lab/evaluationovertime

공식 코드

Evaluating Model Performance in Medical Datasets Over Time

https://github.com/acotai/kunpeng

공식 코드

KUNPENG: An Embodied Large Model for Intelligent Maritime

https://github.com/adamdad/dery

공식 코드

Deep Model Reassembly

https://github.com/adamdad/repfusion

공식 코드

Diffusion Model as Representation Learner

https://github.com/adap/flower

공식 코드

Model-Contrastive Federated Learning

https://github.com/adebayoj/explaindebug

공식 코드

Debugging Tests for Model Explanations

https://github.com/adi3e08/physics_informed_model_based_rl

공식 코드

Physics-Informed Model-Based Reinforcement Learning

https://github.com/adjidieng/DETM

공식 코드

The Dynamic Embedded Topic Model

https://github.com/adriarm/robustness_input_gradients

공식 코드

Characterizing Model Robustness via Natural Input Gradients

https://github.com/adrida/deltaxplainer

공식 코드

Dynamic Interpretability for Model Comparison via Decision Rules

https://github.com/afperezm/acoustic-images-distillation

공식 코드

Audio-Visual Model Distillation Using Acoustic Images

https://github.com/agaldran/mhml_calibration

공식 코드

Multi-Head Multi-Loss Model Calibration

https://github.com/agarwalishika/delift

공식 코드

DELIFT: Data Efficient Language model Instruction Fine Tuning

https://github.com/agiresearch/up5

공식 코드

UP5: Unbiased Foundation Model for Fairness-aware Recommendation

https://github.com/agosiewska/epp-meta-score

공식 코드

Interpretable Meta-Measure for Model Performance

https://github.com/agroboticsresearch/sdm-d

공식 코드

Learn from Foundation Model: Fruit Detection Model without Manual Annotation

https://github.com/aheldis/Cross-model-correlation

공식 코드

Exploring Cross-model Neuronal Correlations in the Context of Predicting Model Performance and Generalizability

https://github.com/ahmed-elliethy/fast-regression-mpc

공식 코드

Fast Adaptive Regression-based Model Predictive Control

https://github.com/ahmeshaf/model_in_coref

공식 코드

How Good is the Model in Model-in-the-loop Event Coreference Resolution Annotation?

https://github.com/ai-planning/macq

공식 코드

MACQ: A Holistic View of Model Acquisition Techniques

https://github.com/ai4life-group/openxai

공식 코드

OpenXAI: Towards a Transparent Evaluation of Model Explanations

https://github.com/aidos-lab/CFGGME

공식 코드

Curvature Filtrations for Graph Generative Model Evaluation

https://github.com/ailiaili/difference_mean_fair_models

공식 코드

Optimising Equal Opportunity Fairness in Model Training

https://github.com/aim-intelligence/repbend

공식 코드

Representation Bending for Large Language Model Safety

https://github.com/aim-uofa/fadiff

공식 코드

Floating Anchor Diffusion Model for Multi-motif Scaffolding

https://github.com/aim-uofa/rgm

공식 코드

RGM: A Robust Generalizable Matching Model

https://github.com/aim3-ruc/movielc

공식 코드

Knowledge Enhanced Model for Live Video Comment Generation

https://github.com/aimotionlab-sztaki/orthogonal-augmentation

공식 코드

Orthogonal projection-based regularization for efficient model augmentation

https://github.com/aiot-lab/neurodet

공식 코드

Unfolding Target Detection with State Space Model

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