大模型对齐与安全 - arXivDaily 专题

2301.05763 2023-08-28 cs.LG 57%

A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows

Line Pouchard, Kristofer G. Reyes, Francis J. Alexander, Byung-Jun Yoon

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

2308.02765 2023-08-08 eess.SY cs.AI cs.SY 57%

Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control

Runze Lin, Yangyang Luo, Xialai Wu, Junghui Chen, Biao Huang, Lei Xie, Hongye Su

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

2205.10060 2023-07-21 cs.LG cs.NE stat.ML 57%

The Unreasonable Effectiveness of Deep Evidential Regression

Nis Meinert, Jakob Gawlikowski, Alexander Lavin

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 11 pages, 25 figures

Journal ref AAAI, vol. 37, no. 8, pp. 9134-9142, Jun. 2023

2307.05519 2023-07-13 q-bio.QM cs.AI cs.CV eess.IV 57%

Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis

Xiaoyi Ji, Richard Salmon, Nita Mulliqi, Umair Khan, Yinxi Wang, Anders Blilie, Henrik Olsson, Bodil Ginnerup Pedersen, Karina Dalsgaard Sørensen, Benedicte Parm Ulhøi, Svein R Kjosavik, Emilius AM Janssen, Mattias Rantalainen, Lars Egevad, Pekka Ruusuvuori, Martin Eklund, Kimmo Kartasalo

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

2307.02367 2023-07-06 cs.LG physics.acc-ph 57%

Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions

Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton, Chris Pappas, Dan Lu, Jared Walden, Majdi I. Radaideh, Sarah Cousineau, Sudarshan Harave

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2306.15887 2023-06-29 cs.AI 57%

Beyond the Hype: Assessing the Performance, Trustworthiness, and Clinical Suitability of GPT3.5

Salmonn Talebi, Elizabeth Tong, Mohammad R. K. Mofrad

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

2306.08891 2023-06-16 cs.CL 57%

Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generation

Zihui Gu, Ju Fan, Nan Tang, Songyue Zhang, Yuxin Zhang, Zui Chen, Lei Cao, Guoliang Li, Sam Madden, Xiaoyong Du

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

Comments Working in progress

2306.07171 2023-06-13 cs.LG cs.DB 57%

Shapley Value on Probabilistic Classifiers

Xiang Li, Haocheng Xia, Jinfei Liu

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

2306.04663 2023-06-09 eess.SP cs.LG 57%

U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging

Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse, Dries Testelmans, Mihaela van der Schaar, Maarten De Vos

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2305.14872 2023-06-01 cs.LG cs.SE 57%

Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning

Janek Groß, Michael Kläs, Lisa Jöckel, Pascal Gerber

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments 8 pages, 7 figures, VERDI workshop collocated with the DSN conference 2023

2210.12760 2023-05-24 cs.LG 57%

On double-descent in uncertainty quantification in overparametrized models

Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová

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

Journal ref Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (2023), PMLR 206:7089-7125

2304.11633 2023-04-25 cs.CL 57%

Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

Bo Li, Gexiang Fang, Yang Yang, Quansen Wang, Wei Ye, Wen Zhao, Shikun Zhang

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

2303.16866 2023-03-30 cs.LG cs.CV 57%

ALUM: Adversarial Data Uncertainty Modeling from Latent Model Uncertainty Compensation

Wei Wei, Jiahuan Zhou, Hongze Li, Ying Wu

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

Comments 10 pages, 5 figures

2303.04340 2023-03-09 cs.LG cs.CV cs.DC cs.RO 57%

Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles

Muzi Peng, Jiangwei Wang, Dongjin Song, Fei Miao, Lili Su

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2202.01840 2023-02-22 cs.LG 57%

Hidden Heterogeneity: When to Choose Similarity-Based Calibration

Kiri L. Wagstaff, Thomas G. Dietterich

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

Comments 22 pages, 8 figures

Journal ref Transactions on Machine Learning Research, January 2023

2210.09150 2023-02-16 cs.CL 57%

Prompting GPT-3 To Be Reliable

Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan Boyd-Graber, Lijuan Wang

专题命中幻觉与事实性：safety(abstract)；分类 cs.CL

Comments ICLR 2023

2302.02595 2023-02-07 cs.LG 57%

Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification

Cameron Gruich, Varun Madhavan, Yixin Wang, Bryan Goldsmith

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

Comments 28 pages, 16 figures (8 main text, 8 SI), submitted to Machine Learning: Science & Technology journal (MLST, IOP)

2301.08914 2023-01-24 cs.CL 57%

ExClaim: Explainable Neural Claim Verification Using Rationalization

Sai Gurrapu, Lifu Huang, Feras A. Batarseh

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

Comments Published at 2022 IEEE 29th STC

2206.00002 2023-01-11 eess.IV cs.CV cs.LG 57%

Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image

Lucy Nwosu, Xiangfang Li, Lijun Qian, Seungchan Kim, Xishuang Dong

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2212.14709 2023-01-02 cs.LG cond-mat.mtrl-sci 57%

A Learning-Based Optimal Uncertainty Quantification Method and Its Application to Ballistic Impact Problems

Xingsheng Sun, Burigede Liu

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

2212.08370 2022-12-19 cs.LG 57%

Shapley variable importance cloud for machine learning models

Yilin Ning, Mingxuan Liu, Nan Liu

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

2211.08701 2022-11-17 cs.RO cs.CV cs.LG 57%

Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction

Masha Itkina, Mykel J. Kochenderfer

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments Conference on Robot Learning (CoRL) 2022, 15 pages, 4 figures

2210.17030 2022-11-03 q-fin.CP cs.LG 57%

Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty

Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami

专题命中幻觉与事实性：safety(abstract)；分类 cs.LG

Comments IEEE BIGDATA 2022 Accepted

2208.03284 2022-11-02 hep-ex cs.LG hep-ph stat.ML 57%

Interpretable Uncertainty Quantification in AI for HEP

Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, Michael Kagan, Brian Nord, Nesar Ramachandra

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

Comments Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

2210.14488 2022-10-27 stat.ML cs.LG cs.NA math.NA nlin.CD physics.ao-ph 57%

History-Based, Bayesian, Closure for Stochastic Parameterization: Application to Lorenz '96

Mohamed Aziz Bhouri, Pierre Gentine

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

2210.12220 2022-10-25 cs.HC cs.LG 57%

Considerations for Visualizing Uncertainty in Clinical Machine Learning Models

Caitlin F. Harrigan, Gabriela Morgenshtern, Anna Goldenberg, Fanny Chevalier

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

Comments Prepared for the CHI 2021 Workshop: Realizing AI in Healthcare: Challenges Appearing in the Wild https://dl.acm.org/doi/10.1145/3411763.3441347

2205.14094 2022-10-25 cs.AI 57%

Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

Melanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

Comments Published in Transactions on Machine Learning Research (10/2022)

Journal ref Transactions on Machine Learning Research (10/2022)

2210.10526 2022-10-20 cs.LG cs.SD eess.AS 57%

Propagating Variational Model Uncertainty for Bioacoustic Call Label Smoothing

Georgios Rizos, Jenna Lawson, Simon Mitchell, Pranay Shah, Xin Wen, Cristina Banks-Leite, Robert Ewers, Bjoern W. Schuller

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

2210.10160 2022-10-20 cs.LG 57%

Uncertainty in Extreme Multi-label Classification

Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhong, Cho-Jui Hsieh, Hsiang-Fu Yu

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

Comments 14 pages, 1 figure, 8 tables

2210.09467 2022-10-19 cs.IR cs.AI 57%

Adversarial and Safely Scaled Question Generation

Sreehari Sankar, Zhihang Dong

专题命中幻觉与事实性：safety(abstract)；分类 cs.AI

Comments 15 pages, 8 figures, 2 tables

1. 幻觉与事实性 1756 篇

A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows

Surrogate Empowered Sim2Real Transfer of Deep Reinforcement Learning for ORC Superheat Control

The Unreasonable Effectiveness of Deep Evidential Regression

Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis

Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions

Beyond the Hype: Assessing the Performance, Trustworthiness, and Clinical Suitability of GPT3.5

Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generation

Shapley Value on Probabilistic Classifiers

U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging

Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning

On double-descent in uncertainty quantification in overparametrized models

Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness

ALUM: Adversarial Data Uncertainty Modeling from Latent Model Uncertainty Compensation

Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles

Hidden Heterogeneity: When to Choose Similarity-Based Calibration

Prompting GPT-3 To Be Reliable

Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification

ExClaim: Explainable Neural Claim Verification Using Rationalization

Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image

A Learning-Based Optimal Uncertainty Quantification Method and Its Application to Ballistic Impact Problems

Shapley variable importance cloud for machine learning models

Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction

Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty

Interpretable Uncertainty Quantification in AI for HEP

History-Based, Bayesian, Closure for Stochastic Parameterization: Application to Lorenz '96

Considerations for Visualizing Uncertainty in Clinical Machine Learning Models

Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

Propagating Variational Model Uncertainty for Bioacoustic Call Label Smoothing

Uncertainty in Extreme Multi-label Classification

Adversarial and Safely Scaled Question Generation