https://github.com/chessbean1/gui-robust
공식 코드GUI-Robust: A Comprehensive Dataset for Testing GUI Agent Robustness in Real-World Anomalies
Papers with Code 아카이브
Data-free Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 2
- 보존된 평가 기록
- 8
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chirag-w/qpsq-learning
공식 코드https://github.com/chris-n-self/large-scale-qml
공식 코드Quantum machine learning of large datasets using randomized measurements
https://github.com/christopher-br/cbrnet
공식 코드Using representation balancing to learn conditional-average dose responses from clustered data
https://github.com/christopherbrix/vnncomp2023_benchmarks
공식 코드https://github.com/christos42/Enhancing-Biomedical-Knowledge-Discovery-for-Diseases
공식 코드https://github.com/cipriantruica/T2K2D2_Benchmark
공식 코드https://github.com/citynet-at-git/Citynet-phase1
공식 코드CityNet: A Comprehensive Multi-Modal Urban Dataset for Advanced Research in Urban Computing
https://github.com/ckkelvinchan/realbasicvsr
공식 코드Investigating Tradeoffs in Real-World Video Super-Resolution
https://github.com/ckoorosh/robutext
공식 코드https://github.com/clarin-pl/lepiszcze
공식 코드This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish
https://github.com/claws-lab/mmsoc
공식 코드MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms
https://github.com/clementchadebec/benchmark_VAE
공식 코드Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case
https://github.com/climsocana/tecb-de
공식 코드https://github.com/clinc/oos-eval
공식 코드An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
https://github.com/clinicalml/mimic_annotations
공식 코드Robust Benchmarking for Machine Learning of Clinical Entity Extraction
https://github.com/clvoloshin/COBS
공식 코드Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning
https://github.com/clvoloshin/OPE-tools
공식 코드Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning
https://github.com/cmrxrecon/cmrxrecon2024
공식 코드https://github.com/cnap/grammaticality-metrics
공식 코드There's No Comparison: Reference-less Evaluation Metrics in Grammatical Error Correction
https://github.com/codalab/codabench
공식 코드Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform
https://github.com/codalab/competitions-v2
공식 코드Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform
https://github.com/codectr/refinectr
공식 코드A Comprehensive Summarization and Evaluation of Feature Refinement Modules for CTR Prediction
https://github.com/codeeff/ecco
공식 코드ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
https://github.com/coder-jzq/radka-css
공식 코드Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech Synthesis
https://github.com/codereef-ai/client
공식 코드https://github.com/coderj-one/giraffe-bench
공식 코드Benchmarking Sequential Visual Input Reasoning and Prediction in Multimodal Large Language Models
https://github.com/coir-team/coir
공식 코드CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
https://github.com/cola-laboratory/omnigenbench
공식 코드OmniGenBench: A Modular Platform for Reproducible Genomic Foundation Models Benchmarking
https://github.com/collinskatie/structured_flexible_and_robust
공식 코드https://github.com/columbia-icsl/tdbench
공식 코드TDBench: Benchmarking Vision-Language Models in Understanding Top-Down Images
https://github.com/commit-0/commit0
공식 코드https://github.com/compl-ai/compl-ai
공식 코드https://github.com/computationalprivacy/mia_llms_benchmark
공식 코드SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)
https://github.com/computernetworks-ufrgs/aedes_detector_smartphone_app_paper
공식 코드https://github.com/conglu1997/v-d4rl
공식 코드Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.