https://github.com/richard-peng-xia/Chinese-Noisy-Text
공식 코드Chinese grammatical error correction based on knowledge distillation
Papers with Code 아카이브
Knowledge Distillation
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Knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/richard-peng-xia/KD-CGEC
공식 코드Chinese grammatical error correction based on knowledge distillation
https://github.com/richardcui18/mia_in_kd
공식 코드https://github.com/richarizardd/self-supervised-vit-path
공식 코드Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology
https://github.com/richterleo/Auditing_Test_for_LMs
공식 코드An Auditing Test To Detect Behavioral Shift in Language Models
https://github.com/riiid/ppap
공식 코드https://github.com/rijgersberg/geitje
공식 코드https://github.com/rikeilong/mcd-foravqa
공식 코드Answering Diverse Questions via Text Attached with Key Audio-Visual Clues
https://github.com/risabbiswas/knowledge-distillation-in-medical-image-segmentation
공식 코드Multi-Task Multi-Scale Contrastive Knowledge Distillation for Efficient Medical Image Segmentation
https://github.com/ristea/fast-aed
공식 코드Lightning Fast Video Anomaly Detection via Adversarial Knowledge Distillation
https://github.com/ritatanz/sav
공식 코드Towards Student Actions in Classroom Scenes: New Dataset and Baseline
https://github.com/rivas-lab/Smiles2Dock
공식 코드Smiles2Dock: an open large-scale multi-task dataset for ML-based molecular docking
https://github.com/rkarmaka/SoftPQ
공식 코드SoftPQ: Robust Instance Segmentation Evaluation via Soft Matching and Tunable Thresholds
https://github.com/rl-vig/libfewshot
공식 코드https://github.com/rll-research/b-pref
공식 코드B-Pref: Benchmarking Preference-Based Reinforcement Learning
https://github.com/rllab/rllab
공식 코드Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/roadonep/eccv2024_mbs
공식 코드Mitigating Background Shift in Class-Incremental Semantic Segmentation
https://github.com/robbie-xu/cpsd
공식 코드Boosting Multi-Label Image Classification with Complementary Parallel Self-Distillation
https://github.com/robfiras/loco-mujoco
공식 코드LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion
https://github.com/robin-janssen/codes-benchmark
공식 코드https://github.com/robshahla/VisQUIC
공식 코드Exploring QUIC Dynamics: A Large-Scale Dataset for Encrypted Traffic Analysis
https://github.com/robustseg/robustseg
공식 코드Robust Multimodal Segmentation with Representation Regularization and Hybrid Prototype Distillation
https://github.com/rockylzy/textdefender
공식 코드Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution
https://github.com/roeltim/ml-leaderboard-position-paper
공식 코드A Position Paper on the Automatic Generation of Machine Learning Leaderboards
https://github.com/rogerferrod/crodino-kd
공식 코드https://github.com/rohban-lab/swinchex
공식 코드SwinCheX: Multi-label classification on chest X-ray images with transformers
https://github.com/rohit901/VANE-Bench
공식 코드VANE-Bench: Video Anomaly Evaluation Benchmark for Conversational LMMs
https://github.com/rolnicklab/imagenetbiodiversity
공식 코드https://github.com/romanenkova95/principledcpd
공식 코드Deep learning model solves change point detection for multiple change types
https://github.com/rorozhl/mmkd
공식 코드Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning
https://github.com/roryshao/dfkd-fgvc
공식 코드Data-free Knowledge Distillation for Fine-grained Visual Categorization
https://github.com/roth-andreas/distilling-influences
공식 코드Distilling Influences to Mitigate Prediction Churn in Graph Neural Networks
https://github.com/roudimit/c2kd
공식 코드C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval
https://github.com/roundfacej/omni
공식 코드https://github.com/rovislab/loopdb
공식 코드LoopDB: A Loop Closure Dataset for Large Scale Simultaneous Localization and Mapping
https://github.com/roymiles/ITRD
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.