https://github.com/rabbit-magic-wh/InDL
공식 코드InDL: A New Dataset and Benchmark for In-Diagram Logic Interpretation based on Visual Illusion
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/radzim/obfuscated
공식 코드https://github.com/ragib-amin-nihal/c2a
공식 코드https://github.com/ragmeh11/qu-brats
공식 코드https://github.com/rahulsrma26/phonetic-word-embedding
공식 코드https://github.com/raiiyf/diffusets_exp
공식 코드https://github.com/rainavyas/attack-comparative-assessment
공식 코드Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment
https://github.com/rainysponge/split-learning-attacks
공식 코드https://github.com/ralschoop/deepus
공식 코드https://github.com/ralucaj/dermx-benchmark
공식 코드Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks
https://github.com/rampasek/HGNet
공식 코드Hierarchical graph neural nets can capture long-range interactions
https://github.com/raphaelmemmesheimer/simitate
공식 코드https://github.com/raulsenaferreira/prdc_2021_sut_module
공식 코드Benchmarking Safety Monitors for Image Classifiers with Machine Learning
https://github.com/raymond-qiancx/dyncim
공식 코드DynCIM: Dynamic Curriculum for Imbalanced Multimodal Learning
https://github.com/rbrandt1/precise-benchmarking-of-xai
공식 코드https://github.com/rcap107/retrieve-merge-predict
공식 코드https://github.com/rcap107/starmie
공식 코드https://github.com/rcap107/yadl
공식 코드https://github.com/recovercoalition/recover
공식 코드https://github.com/recsys-benchmark/daisyrec-v2.0
공식 코드DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
https://github.com/reczoo/BARS
공식 코드BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
https://github.com/reliable-information-lab-hevs/benchmark_llm_texts_detection
공식 코드LLM Detectors Still Fall Short of Real World: Case of LLM-Generated Short News-Like Posts
https://github.com/reml-lab/URSABench
공식 코드https://github.com/remotebiosensing/rppg
공식 코드Remote Bio-Sensing: Open Source Benchmark Framework for Fair Evaluation of rPPG
https://github.com/respiratory-support/respiratory-interventions
공식 코드https://github.com/retailmarketingai/retailsynth
공식 코드RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluation
https://github.com/reubenjrouse/VCap_CapsuleVision2024
공식 코드Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy
https://github.com/revdotcom/speech-datasets
공식 코드https://github.com/rgeirhos/dataset-pruning-metrics
공식 코드Beyond neural scaling laws: beating power law scaling via data pruning
https://github.com/rgeirhos/shortcut-perspective
공식 코드https://github.com/rhermary/plume
공식 코드Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation
https://github.com/ricgama/maenvs4vrp
공식 코드https://github.com/richard-guyunqi/BlenderGym-Open
공식 코드BlenderGym: Benchmarking Foundational Model Systems for Graphics Editing
https://github.com/richterleo/Auditing_Test_for_LMs
공식 코드An Auditing Test To Detect Behavioral Shift in Language Models
https://github.com/rijgersberg/geitje
공식 코드https://github.com/ritatanz/sav
공식 코드Towards Student Actions in Classroom Scenes: New Dataset and Baseline
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.