https://github.com/lcs2-iiitd/gothate
공식 코드Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment
Papers with Code 아카이브
Benchmarking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 2
- 보존된 평가 기록
- 2
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lcs2-iiitd/hatefinetune
공식 코드Probing Critical Learning Dynamics of PLMs for Hate Speech Detection
https://github.com/learnedsystems/SOSD
공식 코드https://github.com/legaldocumentprocessing/fir_dataset_icdar2023
공식 코드https://github.com/leiluk1/codesearcher
공식 코드https://github.com/leogrin/tabular-benchmark
공식 코드Why do tree-based models still outperform deep learning on tabular data?
https://github.com/leoiv/bencher
공식 코드Bencher: Simple and Reproducible Benchmarking for Black-Box Optimization
https://github.com/leolee99/injecguard
공식 코드InjecGuard: Benchmarking and Mitigating Over-defense in Prompt Injection Guardrail Models
https://github.com/leolyliu/HOI4D-Instructions
공식 코드HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interaction
https://github.com/leonchou5311/counterfactual-benchmark
공식 코드Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black Box
https://github.com/leonnnop/var
공식 코드https://github.com/letian2003/c-vqa
공식 코드What If the TV Was Off? Examining Counterfactual Reasoning Abilities of Multi-modal Language Models
https://github.com/lewisclifton/mamba-wbc-classification
공식 코드Mamba-Based Ensemble learning for White Blood Cell Classification
https://github.com/lfrison/i4b
공식 코드Constrained Reinforcement Learning for Safe Heat Pump Control
https://github.com/li-fangyu/sequential_rec
공식 코드Improving Sequential Recommendation Models with an Enhanced Loss Function
https://github.com/liamjdavis/sudoku-smt-solvers
공식 코드Evaluating SAT and SMT Solvers on Large-Scale Sudoku Puzzles
https://github.com/liaopeiyuan/artbench
공식 코드The ArtBench Dataset: Benchmarking Generative Models with Artworks
https://github.com/liaorongfan/deeppersonality
공식 코드https://github.com/liar-zzy/benchmarking-ultra-high-definition-single-image-reflection-removal
공식 코드https://github.com/lidiagarrucho/mama-mia
공식 코드A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations
https://github.com/lifelong-ml/offline-compositional-rl-datasets
공식 코드Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning
https://github.com/lifelonglab/m2i_i2m_benchmark
공식 코드From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning
https://github.com/lightning-uq-box/lightning-uq-box
공식 코드Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning
https://github.com/likaixin2000/mmcode
공식 코드https://github.com/likyoo/open-cd
공식 코드https://github.com/liminxian/DukeMTMC-SI-Tracklet
공식 코드https://github.com/lin-rany/codeIF
공식 코드https://github.com/lina-usc/jansen-rit-model-benchmarking-deep-learning
공식 코드Deep Jansen-Rit Parameter Inference for Model-Driven Analysis of Brain Activity
https://github.com/lingjuanlv/FPPDL
공식 코드https://github.com/linglongqian/csai
공식 코드Knowledge Enhanced Conditional Imputation for Healthcare Time-series
https://github.com/lingxitong/CAMELYON-PLUS-BENCHMARK
공식 코드Towards a Comprehensive Benchmark for Pathological Lymph Node Metastasis in Breast Cancer Sections
https://github.com/linhaowei1/clog
공식 코드CLoG: Benchmarking Continual Learning of Image Generation Models
https://github.com/linhaowei1/kumo
공식 코드Generative Evaluation of Complex Reasoning in Large Language Models
https://github.com/linxins97/nlpbench
공식 코드NLPBench: Evaluating Large Language Models on Solving NLP Problems
https://github.com/linzhiqiu/t2v_metrics
공식 코드GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation
https://github.com/liqinye/sidyp
공식 코드Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.