no code implementations • 3 Jun 2023 • Long Chen, Siyu Teng, Bai Li, Xiaoxiang Na, Yuchen Li, Zixuan Li, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their promise for enhanced safety, efficiency, and economic benefits.
no code implementations • 30 Mar 2023 • Long Chen, Yuchen Li, Chao Huang, Bai Li, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Xiaoxiang Na, Zixuan Li, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits.
no code implementations • 17 Mar 2023 • Siyu Teng, Xuemin Hu, Peng Deng, Bai Li, Yuchen Li, Dongsheng Yang, Yunfeng Ai, Lingxi Li, Zhe XuanYuan, Fenghua Zhu, Long Chen
Intelligent vehicles (IVs) have gained worldwide attention due to their increased convenience, safety advantages, and potential commercial value.
1 code implementation • 20 Jul 2022 • Bai Li
This has led many to question the relevance of linguistics for modern natural language processing.
1 code implementation • Findings (ACL) 2022 • Zining Zhu, Jixuan Wang, Bai Li, Frank Rudzicz
As large and powerful neural language models are developed, researchers have been increasingly interested in developing diagnostic tools to probe them.
1 code implementation • ACL 2022 • Bai Li, Zining Zhu, Guillaume Thomas, Frank Rudzicz, Yang Xu
Second, in a "Jabberwocky" priming-based experiment, we find that LMs associate ASCs with meaning, even in semantically nonsensical sentences.
1 code implementation • IEEE Transactions on Intelligent Transportation Systems 2022 • Bai Li, Yakun Ouyang, Li Li, Youmin Zhang
This paper is focused on the trajectory planning task for autonomous driving on a curvy road.
1 code implementation • 13 Jul 2021 • Zining Zhu, Bai Li, Yang Xu, Frank Rudzicz
As the numbers of submissions to conferences grow quickly, the task of assessing the quality of academic papers automatically, convincingly, and with high accuracy attracts increasing attention.
1 code implementation • ACL 2021 • Bai Li, Zining Zhu, Guillaume Thomas, Yang Xu, Frank Rudzicz
Transformer language models have shown remarkable ability in detecting when a word is anomalous in context, but likelihood scores offer no information about the cause of the anomaly.
1 code implementation • NAACL (CMCL) 2021 • Bai Li, Frank Rudzicz
In this paper, we describe our submission to the CMCL 2021 shared task on predicting human reading patterns.
no code implementations • 23 Sep 2020 • Bai Li
Classical Chinese is a language notable for its word class flexibility: the same word may often be used as a noun or a verb.
2 code implementations • EMNLP 2020 • Bai Li, Guillaume Thomas, Yang Xu, Frank Rudzicz
Word class flexibility refers to the phenomenon whereby a single word form is used across different grammatical categories.
no code implementations • 4 Jun 2020 • Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin
Current neural-network-based classifiers are susceptible to adversarial examples.
1 code implementation • 6 Mar 2020 • Bai Li, Shiqi Wang, Yunhan Jia, Yantao Lu, Zhenyu Zhong, Lawrence Carin, Suman Jana
Recent research has proposed the lottery ticket hypothesis, suggesting that for a deep neural network, there exist trainable sub-networks performing equally or better than the original model with commensurate training steps.
2 code implementations • CVPR 2020 • Yantao Lu, Yunhan Jia, Jian-Yu Wang, Bai Li, Weiheng Chai, Lawrence Carin, Senem Velipasalar
Neural networks are known to be vulnerable to carefully crafted adversarial examples, and these malicious samples often transfer, i. e., they remain adversarial even against other models.
no code implementations • 20 Nov 2019 • Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin
We propose a novel graph-driven generative model, that unifies multiple heterogeneous learning tasks into the same framework.
no code implementations • WS 2020 • Bai Li, Jing Yi Xie, Frank Rudzicz
Tone is a prosodic feature used to distinguish words in many languages, some of which are endangered and scarcely documented.
no code implementations • 27 Aug 2019 • Bai Li, Nanyi Jiang, Joey Sham, Henry Shi, Hussein Fazal
In this paper, we present a real-world conversational AI system to search for and book hotels through text messaging.
no code implementations • NAACL 2019 • Kathleen C. Fraser, Nicklas Linz, Bai Li, Kristina Lundholm Fors, Frank Rudzicz, Alex K{\"o}nig, ra, Alex, Jan ersson, Philippe Robert, Dimitrios Kokkinakis
There is growing evidence that changes in speech and language may be early markers of dementia, but much of the previous NLP work in this area has been limited by the size of the available datasets.
no code implementations • 15 May 2019 • Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin
Adversarial examples are carefully perturbed in-puts for fooling machine learning models.
no code implementations • ICLR 2019 • Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin
In this paper, we propose a powerful second-order attack method that reduces the accuracy of the defense model by Madry et al. (2017).
no code implementations • NAACL 2019 • Bai Li, Yi-Te Hsu, Frank Rudzicz
Machine learning has shown promise for automatic detection of Alzheimer's disease (AD) through speech; however, efforts are hampered by a scarcity of data, especially in languages other than English.
no code implementations • ICLR 2019 • Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin
Sequence-to-sequence models are commonly trained via maximum likelihood estimation (MLE).
3 code implementations • NeurIPS 2019 • Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin
The existence of adversarial data examples has drawn significant attention in the deep-learning community; such data are seemingly minimally perturbed relative to the original data, but lead to very different outputs from a deep-learning algorithm.
no code implementations • 11 Aug 2018 • Bai Li, Ran Zhang, Frank Rudzicz
We replicate a variation of the image captioning architecture by Vinyals et al. (2015), then introduce dropout during inference mode to simulate the effects of neurodegenerative diseases like Alzheimer's disease (AD) and Wernicke's aphasia (WA).
no code implementations • 29 May 2018 • Changyou Chen, Ruiyi Zhang, Wenlin Wang, Bai Li, Liqun Chen
There has been recent interest in developing scalable Bayesian sampling methods such as stochastic gradient MCMC (SG-MCMC) and Stein variational gradient descent (SVGD) for big-data analysis.
no code implementations • 25 Dec 2017 • Bai Li, Changyou Chen, Hao liu, Lawrence Carin
Significant success has been realized recently on applying machine learning to real-world applications.