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Benchmarking

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/jrnlp/multi-eup

공식 코드

Multi-EuP: The Multilingual European Parliament Dataset for Analysis of Bias in Information Retrieval

https://github.com/jsalbert/biotorch

공식 코드

Benchmarking the Accuracy and Robustness of Feedback Alignment Algorithms

https://github.com/jsandersen/cmt

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Efficient, Uncertainty-based Moderation of Neural Networks Text Classifiers

https://github.com/jswati31/cuda-ghr

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CUDA-GHR: Controllable Unsupervised Domain Adaptation for Gaze and Head Redirection

https://github.com/jszheng21/race

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Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models

https://github.com/juanhui28/heart

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Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking

https://github.com/julfrey/detailview

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Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset

https://github.com/juliagast/tgb2

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TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs

https://github.com/julianagonzalezastudillo/netfeat

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Feature interpretability in BCIs: exploring the role of network lateralization

https://github.com/junhongmit/H2GB

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When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark

https://github.com/junjie99/mlvu

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MLVU: Benchmarking Multi-task Long Video Understanding

https://github.com/jusperlee/audiotrust

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AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models

https://github.com/justinkay/aldi

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Align and Distill: Unifying and Improving Domain Adaptive Object Detection

https://github.com/justinwjl/gtb-dti

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Benchmark on Drug Target Interaction Modeling from a Structure Perspective

https://github.com/jviquerat/beacon

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Beacon, a lightweight deep reinforcement learning benchmark library for flow control

https://github.com/jwaladhamala/BOLD-Bias-in-open-ended-language-generation

공식 코드

BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation

https://github.com/jybai/generative-memorization-benchmark

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On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition

https://github.com/k-stacke/ssl-pathology

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Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications

https://github.com/kacperChwialkowski/wildBootstrap

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A Wild Bootstrap for Degenerate Kernel Tests

https://github.com/kaczmarj/champkit

공식 코드

Evaluating histopathology transfer learning with ChampKit

https://github.com/kaggarwal/ganRegression

공식 코드

Benchmarking Regression Methods: A comparison with CGAN

https://github.com/kahno/feature_embedding

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Feature embedding in click-through rate prediction

https://github.com/kainmueller-lab/arctique

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Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification

https://github.com/kaistmm/voxsim_trainer

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VoxSim: A perceptual voice similarity dataset

https://github.com/kaiwenw/JoinGym

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JoinGym: An Efficient Query Optimization Environment for Reinforcement Learning

https://github.com/kaka0910/M4Fog

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M4Fog: A Global Multi-Regional, Multi-Modal, and Multi-Stage Dataset for Marine Fog Detection and Forecasting to Bridge Ocean and Atmosphere

https://github.com/kakaobrain/chexgpt

공식 코드

CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling

https://github.com/kamilazdybal/local-manifold-learning

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Local manifold learning and its link to domain-based physics knowledge

https://github.com/kananmahammadli/sllmbo

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Sequential Large Language Model-Based Hyper-parameter Optimization

https://github.com/kanishkamisra/minicons

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minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models

https://github.com/kanishkg/boxing-gym

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BoxingGym: Benchmarking Progress in Automated Experimental Design and Model Discovery

https://github.com/kapilw25/Evaluation_generated_images

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Multimodal Benchmarking and Recommendation of Text-to-Image Generation Models

https://github.com/karim-53/compare-xai

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Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark

https://github.com/karl-zhao/benchmarking-gnns-pyg

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Benchmarking Graph Neural Networks

https://github.com/karttikeya/minrev

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PaReprop: Fast Parallelized Reversible Backpropagation

https://github.com/katarinayuan/structtokenbench

공식 코드

Protein Structure Tokenization: Benchmarking and New Recipe

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