https://github.com/lackel/sdc
Benchmarking Natural Language Understanding Services for building Conversational Agents
Papers with Code 아카이브
Data-free Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lamalab-org/mac-bench
https://github.com/laurendelong21/mars
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs
https://github.com/lavoiems/Cats-UDT
https://github.com/lavoiems/SADt
https://github.com/lavoiems/SPUDT
https://github.com/ldkong1205/PointCloud-C
Benchmarking and Analyzing Point Cloud Classification under Corruptions
https://github.com/lee-zq/3DUNet-Pytorch
https://github.com/leemengwei/my_mmdetection
https://github.com/leffff/graphormer-pyg
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
https://github.com/leo-liuzy/codeupdatearena
CodeUpdateArena: Benchmarking Knowledge Editing on API Updates
https://github.com/leolee99/CLIP_ITM
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/lewandofskee/mambaad
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection
https://github.com/lheim/TFLM-Evaluation
Measuring what Really Matters: Optimizing Neural Networks for TinyML
https://github.com/lheim/TFLM-Toolchain
Measuring what Really Matters: Optimizing Neural Networks for TinyML
https://github.com/lhwcv/mmdet
https://github.com/liangcaisu/stem
BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
https://github.com/lifelong-robot-learning/libero
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
https://github.com/lifu-tu/BenchmarkingApproximateInference
Benchmarking Approximate Inference Methods for Neural Structured Prediction
https://github.com/lijiaman/egoego_release
https://github.com/liketheflower/jimmy_dgl
https://github.com/ling-pan/res
https://github.com/linjieli222/hero_video_feature_extractor
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/linzhiqiu/t2i_metrics
GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation
https://github.com/lippman1125/mmdetection_lqy
https://github.com/lishenghui/ARFL
https://github.com/lizhe960118/CenterNet
https://github.com/lizonghang/leaf-mx
https://github.com/ljjyxz123/mmdetection
https://github.com/llm-council/llm-council
Language Model Council: Democratically Benchmarking Foundation Models on Highly Subjective Tasks
https://github.com/loveheaven/scann
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
https://github.com/lsj2408/Transformer-M
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
https://github.com/ltnghia/ANet
https://github.com/ltnghia/CAMO
https://github.com/lucas-rbnt/bm-mae
https://github.com/luchris429/popjaxrl
POPGym: Benchmarking Partially Observable Reinforcement Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.