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Knowledge Distillation

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하위 태스크: 2
평가표: 11
보존된 평가 기록: 90

Knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.

코드

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

https://github.com/bayer-science-for-a-better-life/data2text-bioleaflets

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Biomedical Data-to-Text Generation via Fine-Tuning Transformers

https://github.com/bbaillif/genbench3d

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Benchmarking structure-based three-dimensional molecular generative models using GenBench3D: ligand conformation quality matters

https://github.com/bbrattoli/ZeroShotVideoClassification

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Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications

https://github.com/bcjaeger/aorsf

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Accelerated and interpretable oblique random survival forests

https://github.com/bdlab-ucd/icebench

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IceBench: A Benchmark for Deep Learning based Sea Ice Type Classification

https://github.com/bearcleverproud/awesomewsi

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A Survey of Pathology Foundation Model: Progress and Future Directions

https://github.com/behavioral-data/blade

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BLADE: Benchmarking Language Model Agents for Data-Driven Science

https://github.com/beijing-aisi/cvc

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CVC: A Large-Scale Chinese Value Rule Corpus for Value Alignment of Large Language Models

https://github.com/beiyan1911/players-iod

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Refined Response Distillation for Class-Incremental Player Detection

https://github.com/belimmer/PerturbationSaliencyEvaluation

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Benchmarking Perturbation-based Saliency Maps for Explaining Atari Agents

https://github.com/bellymonster/Weighted-Soft-Label-Distillation

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Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective

https://github.com/ben-e-walters/neuromorse

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NeuroMorse: A Temporally Structured Dataset For Neuromorphic Computing

https://github.com/benchopt/benchopt

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Benchopt: Reproducible, efficient and collaborative optimization benchmarks

https://github.com/benediktstroebl/agent-evals

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AI Agents That Matter

https://github.com/benevolentAI/guacamol

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GuacaMol: Benchmarking Models for De Novo Molecular Design

https://github.com/benevolentAI/guacamol_baselines

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GuacaMol: Benchmarking Models for De Novo Molecular Design

https://github.com/benjamintowle/pasa

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Learn What Is Possible, Then Choose What Is Best: Disentangling One-To-Many Relations in Language Through Text-based Games

https://github.com/berenslab/dependence-measures-medical-imaging

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Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging

https://github.com/berenslab/retinal-vessel-segmentation-benchmark

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Benchmarking Retinal Blood Vessel Segmentation Models for Cross-Dataset and Cross-Disease Generalization

https://github.com/berkerdemirel/Adjusting-Pretrained-Backbones-for-Performativity

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Adjusting Pretrained Backbones for Performativity

https://github.com/bernard-yang/mmsci_table

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Does Table Source Matter? Benchmarking and Improving Multimodal Scientific Table Understanding and Reasoning

https://github.com/bespontaneous/proteus-pytorch

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Accessing Vision Foundation Models at ImageNet-level Costs

https://github.com/bethgelab/frequency_determines_performance

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No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance

https://github.com/bethgelab/imagecorruptions

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Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

https://github.com/bethgelab/mmdetection

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Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

https://github.com/bethgelab/robust-detection-benchmark

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Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

https://github.com/bethgelab/sort-and-search

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Efficient Lifelong Model Evaluation in an Era of Rapid Progress

https://github.com/bethgelab/stylize-datasets

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Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

https://github.com/bezirganyan/luma

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LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal Data

https://github.com/bgonzalezbustamante/TextClass-Benchmark

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TextClass Benchmark: A Continuous Elo Rating of LLMs in Social Sciences

https://github.com/bhheo/BSS_distillation

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Knowledge Distillation with Adversarial Samples Supporting Decision Boundary

https://github.com/bia006/darts

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DARTS: Double Attention Reference-based Transformer for Super-resolution

https://github.com/bia006/hitsr

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HiTSR: A Hierarchical Transformer for Reference-based Super-Resolution

https://github.com/biasvariancelabs/aitlas

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AiTLAS: Artificial Intelligence Toolbox for Earth Observation

https://github.com/biblenlp/ebible-experiments

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The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages

https://github.com/bidalab/mobileb2c_behavepassdb

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IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C)

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