大模型对齐与安全 - arXivDaily 专题

2105.09474 2021-06-03 cs.LG stat.AP 57%

Quantifying sources of uncertainty in drug discovery predictions with probabilistic models

Stanley E. Lazic, Dominic P. Williams

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 34 pages, 9 figures

Journal ref Artificial Intelligence in the Life Sciences (2021)

2105.14645 2021-06-01 physics.comp-ph cs.LG 57%

Empirical Models for Multidimensional Regression of Fission Systems

Akshay J. Dave, Jiankai Yu, Jarod Wilson, Bren Phillips, Kaichao Sun, Benoit Forget

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 20 pages, 7 figures

2011.08712 2021-05-31 cs.CV cs.LG cs.NE eess.IV 57%

A Simple Framework to Quantify Different Types of Uncertainty in Deep Neural Networks for Image Classification

Aria Khoshsirat

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2104.03834 2021-04-09 cs.LG cs.DC stat.ML 57%

Bayesian Variational Federated Learning and Unlearning in Decentralized Networks

Jinu Gong, Osvaldo Simeone, Joonhyuk Kang

专题命中幻觉与事实性：trustworthy(abstract)；分类 cs.LG

Comments Submitted for conference publication

2103.08349 2021-04-06 cs.LG physics.app-ph 57%

Data-driven method for real-time prediction and uncertainty quantification of fatigue failure under stochastic loading using artificial neural networks and Gaussian process regression

Maor Farid

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2006.06848 2021-03-19 stat.ML cs.LG 57%

Getting a CLUE: A Method for Explaining Uncertainty Estimates

Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato

专题命中幻觉与事实性：trustworthy(abstract)；分类 cs.LG

Comments Accepted as an oral presentation at ICLR 2021

2103.08951 2021-03-17 cs.LG stat.AP 57%

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties

Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 21 pages, 13 Figures

Journal ref Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021

2006.05821 2021-03-16 cs.RO cs.AI eess.SP 57%

Development of A Stochastic Traffic Environment with Generative Time-Series Models for Improving Generalization Capabilities of Autonomous Driving Agents

Anil Ozturk, Mustafa Burak Gunel, Melih Dal, Ugur Yavas, Nazim Kemal Ure

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

Comments 7 pages, 4 figures, 7 tables, IV2020

2101.02974 2021-01-11 cs.LG stat.ML 57%

Approaching Neural Network Uncertainty Realism

Joachim Sicking, Alexander Kister, Matthias Fahrland, Stefan Eickeler, Fabian Hüger, Stefan Rüping, Peter Schlicht, Tim Wirtz

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments Accepted at the NeurIPS 2019 Workshop on Machine Learning for Autonomous Driving (ML4AD)

2010.10969 2021-01-07 cs.LG stat.ML 57%

Incorporating Interpretable Output Constraints in Bayesian Neural Networks

Wanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 11 pages, with six supplementary pages. 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada. Code available at: https://github.com/dtak/ocbnn-public. Updated version (final, official submission to NeurIPS in January 2021) includes post-conference revisions: improved results in Section 6.2, and corrected minor errata in Appendix C

1910.04819 2021-01-05 cs.LG stat.ML 57%

Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation

Theodoros Tsiligkaridis

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments To appear in Neural Networks. https://doi.org/10.1016/j.neunet.2020.12.011

Journal ref Neural Networks, Volume 135, March 2021, Pages 105-114

2010.01440 2020-11-20 cs.LG cs.SD eess.AS q-bio.QM 57%

Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia

Utkarsh Sarawgi, Wazeer Zulfikar, Rishab Khincha, Pattie Maes

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments To appear at NeurIPS Machine Learning for Health (ML4H) 2020

2009.09535 2020-09-22 stat.ML cs.LG 57%

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts

Sehwan Kim, Qifan Song, Faming Liang

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 27 pages

2008.02866 2020-08-18 cs.CV cs.LG eess.IV 57%

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia

Edward Verenich, Alvaro Velasquez, Nazar Khan, Faraz Hussain

专题命中幻觉与事实性：trustworthy(abstract)；分类 cs.LG

Comments 7 pages, 6 figures

2007.03212 2020-07-08 cs.LG stat.ML 57%

Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks

Doyup Lee, Yeongjae Cheon

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments ICML'20 Workshop on Uncertainty and Robustness in Deep Learning

2002.09831 2020-02-25 cs.LG stat.ML 57%

On the Role of Dataset Quality and Heterogeneity in Model Confidence

Yuan Zhao, Jiasi Chen, Samet Oymak

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 25 pages, 14 figures

1905.11659 2020-02-04 cs.LG stat.ML 57%

Evaluating and Calibrating Uncertainty Prediction in Regression Tasks

Dan Levi, Liran Gispan, Niv Giladi, Ethan Fetaya

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2001.10494 2020-01-29 cs.LG cs.SY eess.SY stat.ML 57%

Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems

Feiyang Cai, Xenofon Koutsoukos

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments Accepted by 11th International Conference on Cyber-Physical Systems (ICCPS2020)

2001.00893 2020-01-06 cs.LG stat.ML 57%

Aleatoric and Epistemic Uncertainty with Random Forests

Mohammad Hossein Shaker, Eyke Hüllermeier

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 10 pages, 4 figures

1912.03673 2019-12-10 cs.CV cs.LG stat.ML 57%

Detection of False Positive and False Negative Samples in Semantic Segmentation

Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

1907.00435 2019-09-17 cs.CY 57%

YouTube Chatter: Understanding Online Comments Discourse on Misinformative and Political YouTube Videos

Aarash Heydari, Janny Zhang, Shaan Appel, Xinyi Wu, Gireeja Ranade

专题命中幻觉与事实性：trustworthy(abstract)；分类 cs.CY

Comments 32 pages, 23 figures. Primary contributors: Aarash Heydari and Janny Zhang. These authors contributed equally to the work

1908.11779 2019-09-02 cs.DC cs.AI cs.CR 57%

Analyzing Cyber-Physical Systems from the Perspective of Artificial Intelligence

Eric M. S. P. Veith, Lars Fischer, Martin Tröschel, Astrid Nieße

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

1904.10922 2019-04-25 cs.LG stat.ML 57%

The Scientific Method in the Science of Machine Learning

Jessica Zosa Forde, Michela Paganini

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 4 pages + 1 appendix. Presented at the ICLR 2019 Debugging Machine Learning Models workshop

1803.09186 2019-02-07 math.OC cs.LG 57%

Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System

Ross Boczar, Nikolai Matni, Benjamin Recht

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments Changed margins

1811.03305 2018-12-04 cs.NE cs.CV cs.LG stat.ML 57%

BAR: Bayesian Activity Recognition using variational inference

Ranganath Krishnan, Mahesh Subedar, Omesh Tickoo

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

1802.10501 2018-12-03 stat.ML cs.LG 57%

Predictive Uncertainty Estimation via Prior Networks

Andrey Malinin, Mark Gales

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

1804.06647 2018-04-19 cs.AI cs.MA 57%

Modular Verification of Vehicle Platooning with Respect to Decisions, Space and Time

Maryam Kamali, Sven Linker, Michael Fisher

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

1607.03594 2017-01-24 cs.LG 57%

Estimating Uncertainty Online Against an Adversary

Volodymyr Kuleshov, Stefano Ermon

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

1701.02795 2017-01-12 cs.CL 57%

Bidirectional American Sign Language to English Translation

Hardie Cate, Zeshan Hussain

专题命中幻觉与事实性：alignment(abstract)；分类 cs.CL

Comments 7 pages

cs/0504066 2009-12-01 cs.AI 57%

Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique

Vitaly Schetinin, Jonathan E. Fieldsend, Derek Partridge, Wojtek J. Krzanowski, Richard M. Everson, Trevor C. Bailey, Adolfo Hernandez

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

Journal ref Journal of Mathematical Modelling and Algorithms, 2005

1. 幻觉与事实性 1756 篇

Quantifying sources of uncertainty in drug discovery predictions with probabilistic models

Empirical Models for Multidimensional Regression of Fission Systems

A Simple Framework to Quantify Different Types of Uncertainty in Deep Neural Networks for Image Classification

Bayesian Variational Federated Learning and Unlearning in Decentralized Networks

Data-driven method for real-time prediction and uncertainty quantification of fatigue failure under stochastic loading using artificial neural networks and Gaussian process regression

Getting a CLUE: A Method for Explaining Uncertainty Estimates

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties

Development of A Stochastic Traffic Environment with Generative Time-Series Models for Improving Generalization Capabilities of Autonomous Driving Agents

Approaching Neural Network Uncertainty Realism

Incorporating Interpretable Output Constraints in Bayesian Neural Networks

Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation

Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts

Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia

Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks

On the Role of Dataset Quality and Heterogeneity in Model Confidence

Evaluating and Calibrating Uncertainty Prediction in Regression Tasks

Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems

Aleatoric and Epistemic Uncertainty with Random Forests

Detection of False Positive and False Negative Samples in Semantic Segmentation

YouTube Chatter: Understanding Online Comments Discourse on Misinformative and Political YouTube Videos

Analyzing Cyber-Physical Systems from the Perspective of Artificial Intelligence

The Scientific Method in the Science of Machine Learning

Finite-Data Performance Guarantees for the Output-Feedback Control of an Unknown System

BAR: Bayesian Activity Recognition using variational inference

Predictive Uncertainty Estimation via Prior Networks

Modular Verification of Vehicle Platooning with Respect to Decisions, Space and Time

Estimating Uncertainty Online Against an Adversary

Bidirectional American Sign Language to English Translation

Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique