TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Language Modelling	100 sleep nights of 8 caregivers	Gpt3	10%	1	# 1
Node Classification	Cora (60%/20%/20% random splits)	GCN+JK	1:1 Accuracy	86.90 ± 1.51	# 22
Continuous Control	DeepMind Cheetah Run (Images)	PlaNet	Return	650	# 4
Sign Language Recognition	RWTH-PHOENIX-Weather 2014	SLRGAN	Word Error Rate (WER)	23.4	# 10
Anomaly Detection In Surveillance Videos	ShanghaiTech Weakly Supervised	Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection	AUC-ROC	97.48	# 2

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	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/007-democratically-finding-the-cause-of/language-modelling-on-100-sleep-nights-of-8)](https://paperswithcode.com/sota/language-modelling-on-100-sleep-nights-of-8?p=007-democratically-finding-the-cause-of)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/007-democratically-finding-the-cause-of/anomaly-detection-in-surveillance-videos-on-1)](https://paperswithcode.com/sota/anomaly-detection-in-surveillance-videos-on-1?p=007-democratically-finding-the-cause-of)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/007-democratically-finding-the-cause-of/continuous-control-on-deepmind-cheetah-run)](https://paperswithcode.com/sota/continuous-control-on-deepmind-cheetah-run?p=007-democratically-finding-the-cause-of)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/007-democratically-finding-the-cause-of/sign-language-recognition-on-rwth-phoenix)](https://paperswithcode.com/sota/sign-language-recognition-on-rwth-phoenix?p=007-democratically-finding-the-cause-of)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/007-democratically-finding-the-cause-of/node-classification-on-cora-60-20-20-random)](https://paperswithcode.com/sota/node-classification-on-cora-60-20-20-random?p=007-democratically-finding-the-cause-of)`

007: Democratically Finding The Cause of Packet Drops

20 Feb 2018 · Arzani Behnaz, Ciraci Selim, Chamon Luiz, Zhu Yibo, Liu Hingqiang, Padhye Jitu, Loo Boon Thau, Outhred Geoff ·

Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur. We introduce 007, a lightweight, always-on diagnosis application that can find problematic links and also pinpoint problems for each TCP connection. 007 is completely contained within the end host. During its two month deployment in a tier-1 datacenter, it detected every problem found by previously deployed monitoring tools while also finding the sources of other problems previously undetected.

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