Papers with Code 아카이브

Data-free Knowledge Distillation

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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/jonasschmidinger/limesoda_literature.review

공식 코드

LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping

https://github.com/jonatasbcchagas/aco_thop

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Ants can orienteer a thief in their robbery

https://github.com/jonatasbcchagas/acoplusplus_thop

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Efficiently solving the thief orienteering problem with a max-min ant colony optimization approach

https://github.com/jonathan-roberts1/SciFIBench

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SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation

https://github.com/joonaspu/video-game-behavioural-cloning

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Benchmarking End-to-End Behavioural Cloning on Video Games

https://github.com/josemiki/benchmarking_person_re_id

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Benchmarking person re-identification datasets and approaches for practical real-world implementations

https://github.com/jovasque156/disparisk

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DispaRisk: Auditing Fairness Through Usable Information

https://github.com/joyhsu0504/geoclidean_framework

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Geoclidean: Few-Shot Generalization in Euclidean Geometry

https://github.com/jpeg-aic/dataset-jpeg-ai-sdr25

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Subjective Visual Quality Assessment for High-Fidelity Learning-Based Image Compression

https://github.com/jpfolch/catechol_solvent_selection

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The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning

https://github.com/jpmorganchase/llm-email-spam-detection

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Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection

https://github.com/jppbsi/LibOPT

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LibOPT: An Open-Source Platform for Fast Prototyping Soft Optimization Techniques

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

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

https://github.com/jsalbert/biotorch

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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

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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

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Evaluating histopathology transfer learning with ChampKit

https://github.com/kaggarwal/ganRegression

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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

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.