https://github.com/shashankskagnihotri/benchmarking_robustness
공식 코드Are Synthetic Corruptions A Reliable Proxy For Real-World Corruptions?
Papers with Code 아카이브
Benchmarking
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shashankskagnihotri/cospgd
공식 코드CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
https://github.com/shashidharjavaji/RC_BENCH
공식 코드https://github.com/shaunak27/grain-clip
공식 코드Grounding Descriptions in Images informs Zero-Shot Visual Recognition
https://github.com/shawnan-whu/choice
공식 코드CHOICE: Benchmarking the Remote Sensing Capabilities of Large Vision-Language Models
https://github.com/shehzaadzd/MINERVA
공식 코드Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks
https://github.com/shenyanghuang/tgb
공식 코드TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
https://github.com/shijianjian/ImmersePro
공식 코드ImmersePro: End-to-End Stereo Video Synthesis Via Implicit Disparity Learning
https://github.com/shijieS/SST
공식 코드https://github.com/shijieS/people-counting-dataset
공식 코드Benchmark data and method for real-time people counting in cluttered scenes using depth sensors
https://github.com/shilin-lu/vine
공식 코드Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances
https://github.com/shimazaki/pnlss
공식 코드A projected nonlinear state-space model for forecasting time series signals
https://github.com/shimhz/a_dcf
공식 코드a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification
https://github.com/shiqiyu/opengait
공식 코드LidarGait: Benchmarking 3D Gait Recognition with Point Clouds
https://github.com/shivangi-aneja/COSMOS
공식 코드COSMOS: Catching Out-of-Context Misinformation with Self-Supervised Learning
https://github.com/shiyegao/Self-Contradictory-Instructions-SCI
공식 코드Dissecting Dissonance: Benchmarking Large Multimodal Models Against Self-Contradictory Instructions
https://github.com/shl5133/E2EECPE
공식 코드End-to-end Emotion-Cause Pair Extraction via Learning to Link
https://github.com/showlab/macosworld
공식 코드macOSWorld: A Multilingual Interactive Benchmark for GUI Agents
https://github.com/shubha07m/Energy-optimized-semantic-loss
공식 코드Transformers for Green Semantic Communication: Less Energy, More Semantics
https://github.com/shubha07m/MetaGreen-Meta-Learning-Inspired-Transformer-Selection
공식 코드MetaGreen: Meta-Learning Inspired Transformer Selection for Green Semantic Communication
https://github.com/shuvenduroy/multimodal
공식 코드Benchmarking Vision-Language Contrastive Methods for Medical Representation Learning
https://github.com/shyyhs/CourseraParallelCorpusMining
공식 코드Coursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation
https://github.com/sianalytics/roar
공식 코드On Pitfalls of $\textit{RemOve-And-Retrain}$: Data Processing Inequality Perspective
https://github.com/siddheshih/culture-awareness-llms
공식 코드Survey of Cultural Awareness in Language Models: Text and Beyond
https://github.com/sign-language-processing/pose
공식 코드pose-format: Library for Viewing, Augmenting, and Handling .pose Files
https://github.com/signals-dev/Orion
공식 코드TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
https://github.com/signetlabdei/sharp
공식 코드https://github.com/simarkareer/unifiedvideoda
공식 코드We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline
https://github.com/sinc-lab/rna-llm-folding
공식 코드Comprehensive benchmarking of large language models for RNA secondary structure prediction
https://github.com/sinhala-nlp/nsina
공식 코드https://github.com/sinhala-nlp/sinhala-headline-generation
공식 코드https://github.com/sinhala-nlp/sinhala-news-category-prediction
공식 코드https://github.com/sinhala-nlp/sinhala-news-media-identification
공식 코드https://github.com/sintel-dev/orion
공식 코드AER: Auto-Encoder with Regression for Time Series Anomaly Detection
https://github.com/sisinflab/Ducho-meets-Elliot
공식 코드Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation
https://github.com/sisinflab/datarec
공식 코드DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.