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Data-free Knowledge Distillation

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전체 기법 전체 데이터셋

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/jhoelli/xtsc-bench

공식 코드

XTSC-Bench: Quantitative Benchmarking for Explainers on Time Series Classification

https://github.com/jhu-clsp/analogical-reasoning

공식 코드

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies

https://github.com/ji-cather/graphagent

공식 코드

LLM-Based Multi-Agent Systems are Scalable Graph Generative Models

https://github.com/jia-py/erase

공식 코드

ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems

https://github.com/jiachens/ModelNet40-C

공식 코드

Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions

https://github.com/jiangjyjy/yue-benchmark

공식 코드

How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models

https://github.com/jianhao2016/AllSet

공식 코드

You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks

https://github.com/jiarunliu/biovfm

공식 코드

BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis

https://github.com/jiawei-ren/modelnetc

공식 코드

Benchmarking and Analyzing Point Cloud Classification under Corruptions

https://github.com/jiaweilian/ap-pa

공식 코드

Benchmarking Adversarial Patch Against Aerial Detection

https://github.com/jiaweilian/benchmarking_physical_attack

공식 코드

PADetBench: Towards Benchmarking Physical Attacks against Object Detection

https://github.com/jiaweilian/padetbench

공식 코드

PADetBench: Towards Benchmarking Physical Attacks against Object Detection

https://github.com/jiehonglin/vi-net

공식 코드

VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representations

https://github.com/jimmylihui/OpenGenome

공식 코드

GenBench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models

https://github.com/jind11/HSLN-Joint-Sentence-Classification

공식 코드

Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts

https://github.com/jing-ds/hnn_gad

공식 코드

Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks

https://github.com/jingcheng-du/ML_Net-1

공식 코드

ML-Net: multi-label classification of biomedical texts with deep neural networks

https://github.com/jingkang50/openood

공식 코드

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection

https://github.com/jinglin-liang/dddr

공식 코드

Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning

https://github.com/jingwu6/extended-agriculture-vision-dataset

공식 코드

Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis

https://github.com/jingyi0000/vlm_survey

공식 코드

Vision-Language Models for Vision Tasks: A Survey

https://github.com/jinzhuoran/rag-rewardbench

공식 코드

RAG-RewardBench: Benchmarking Reward Models in Retrieval Augmented Generation for Preference Alignment

https://github.com/jinzhuoran/rwku

공식 코드

RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

https://github.com/jitinkrishnan/transliteration-hindi-malayalam

공식 코드

Cross-Lingual Text Classification of Transliterated Hindi and Malayalam

https://github.com/jlianglab/benchmarktransferlearning

공식 코드

A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis

https://github.com/jmhb0/microvqa

공식 코드

MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific Research

https://github.com/jmiramont/mcsm-benchs

공식 코드

Benchmarking multi-component signal processing methods in the time-frequency plane

https://github.com/jo-wang/otta_vit_survey

공식 코드

In Search of Lost Online Test-time Adaptation: A Survey

https://github.com/job-sdf/benchmark

공식 코드

Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking

https://github.com/joeleelyf/ovo-bench

공식 코드

OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?

https://github.com/joeying1019/ultratool

공식 코드

Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios

https://github.com/joez17/videoniah

공식 코드

Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs

https://github.com/johndmendonca/maia-dqe

공식 코드

Dialogue Quality and Emotion Annotations for Customer Support Conversations

https://github.com/johndmendonca/medal

공식 코드

MEDAL: A Framework for Benchmarking LLMs as Multilingual Open-Domain Chatbots and Dialogue Evaluators

https://github.com/jokersio-tsy/autot2t

공식 코드

Automated Text-to-Table for Reasoning-Intensive Table QA: Pipeline Design and Benchmarking Insights

https://github.com/jonasschmidinger/limesoda_benchmarking

공식 코드

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

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