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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/cap-ntu/FedReID

공식 코드

Optimizing Performance of Federated Person Re-identification: Benchmarking and Analysis

https://github.com/caperock/robustai

공식 코드

Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation

https://github.com/capoe/benchml

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BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scale

https://github.com/cardio-ai/cadp

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Content-Aware Differential Privacy with Conditional Invertible Neural Networks

https://github.com/carkham/fedsd2c

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One-shot Federated Learning via Synthetic Distiller-Distillate Communication

https://github.com/caroladoerr/leadingonedac

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Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration

https://github.com/cartucho/surgt_benchmarking

공식 코드

SurgT challenge: Benchmark of Soft-Tissue Trackers for Robotic Surgery

https://github.com/castorini/ragnarok

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Ragnarök: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track

https://github.com/cathyxl/magic

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MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration

https://github.com/causalens/cdml-neurips2020

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Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data

https://github.com/cavalab/ecg-survival-benchmark

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A Closer Look at Mortality Risk Prediction from Electrocardiograms

https://github.com/cbg-ethz/bmi

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Beyond Normal: On the Evaluation of Mutual Information Estimators

https://github.com/cbg-ethz/subgroupseparation

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High-Dimensional Inference in Bayesian Networks

https://github.com/ccp-eva/sporttaskme22

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Sport Task: Fine Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2022

https://github.com/cemuluoglakci/hypotermqa

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HypoTermQA: Hypothetical Terms Dataset for Benchmarking Hallucination Tendency of LLMs

https://github.com/cevers/sap_locata_eval

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The LOCATA Challenge: Acoustic Source Localization and Tracking

https://github.com/cgoliver/rnaglib

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A Comprehensive Benchmark for RNA 3D Structure-Function Modeling

https://github.com/cgye96/a_closer_look_at_3dfsl

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What Makes for Effective Few-shot Point Cloud Classification?

https://github.com/chakra-et/chakra

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Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

https://github.com/chao1224/geom3d

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Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials

https://github.com/charlesgong12/rece

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Reliable and Efficient Concept Erasure of Text-to-Image Diffusion Models

https://github.com/charsyme/Human-Data-Generation-Framework

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Efficient Realistic Data Generation Framework leveraging Deep Learning-based Human Digitization

https://github.com/chartgalaxy/chartgalaxy

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ChartGalaxy: A Dataset for Infographic Chart Understanding and Generation

https://github.com/chelsea234/hifi_ifdl

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DeepFake-O-Meter v2.0: An Open Platform for DeepFake Detection

https://github.com/chen700564/RGB

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Benchmarking Large Language Models in Retrieval-Augmented Generation

https://github.com/chenfei-liao/multi-modal-semantic-segmentation-robustness-benchmark

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Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness

https://github.com/chengcv/dfrfs

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Disentangled Feature Representation for Few-shot Image Classification

https://github.com/chenguolin/InstructScene

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InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior

https://github.com/chengxuphd/dcr

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DCR: Quantifying Data Contamination in LLMs Evaluation

https://github.com/chengyuehuang511/frames-vqa

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FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering

https://github.com/chengyui/nuwats

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NuwaTS: a Foundation Model Mending Every Incomplete Time Series

https://github.com/chengyuyang-njit/imagedesmoke

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Laparoscopic Image Desmoking Using the U-Net with New Loss Function and Integrated Differentiable Wiener Filter

https://github.com/chenshuang-zhang/imagenet_d

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ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object

https://github.com/chenxing1999/recsys-benchmark

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A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems

https://github.com/chenyi99/egoplan

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EgoPlan-Bench: Benchmarking Multimodal Large Language Models for Human-Level Planning

https://github.com/chenyuen0103/gender-bias

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Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias

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