no code implementations • 15 Nov 2023 • Chenghao Yang, Tuhin Chakrabarty, Karli R Hochstatter, Melissa N Slavin, Nabila El-Bassel, Smaranda Muresan
However, we find that using explanations during modeling leads to a significant boost in classification accuracy demonstrating their beneficial role in a high-stakes domain such as studying the opioid use disorder continuum.
1 code implementation • 24 Oct 2023 • Chenghao Yang, Allyson Ettinger
Understanding sentence meanings and updating information states appropriately across time -- what we call "situational understanding" (SU) -- is a critical ability for human-like AI agents.
no code implementations • 28 Sep 2023 • Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen
The increasing capabilities of large language models (LLMs) raise opportunities for artificial general intelligence but concurrently amplify safety concerns, such as potential misuse of AI systems, necessitating effective AI alignment.
1 code implementation • 31 May 2023 • Chenghao Yang, Fan Yin, He He, Kai-Wei Chang, Xiaofei Ma, Bing Xiang
In practice, Shapley Values are often estimated with a small number of stochastic model evaluations.
2 code implementations • 20 Dec 2022 • Shiqi Wang, Zheng Li, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Dan Roth, Bing Xiang
Most existing works on robustness in text or code tasks have focused on classification, while robustness in generation tasks is an uncharted area and to date there is no comprehensive benchmark for robustness in code generation.
1 code implementation • 19 Oct 2022 • Chenghao Yang, Xuezhe Ma
Despite its superior performance, such fine-tuning can be unstable, resulting in significant variance in performance and potential risks for practical applications.
no code implementations • 23 Jul 2022 • Chenghao Yang, Zhongda Wang, Yinshui Xia, Zhufei Chu
Furthermore, the Transformer and GNNs are adopted as a joint learning policy for the QoR prediction of the unseen circuit-optimization sequences.
1 code implementation • ICLR 2022 • Chenghao Yang, Hongyuan Mei, Jason Eisner
The neural Hawkes process (Mei & Eisner, 2017) is a generative model of irregularly spaced sequences of discrete events.
3 code implementations • 7 Jun 2021 • Xiangyang Mou, Chenghao Yang, Mo Yu, Bingsheng Yao, Xiaoxiao Guo, Saloni Potdar, Hui Su
Recent advancements in open-domain question answering (ODQA), i. e., finding answers from large open-domain corpus like Wikipedia, have led to human-level performance on many datasets.
1 code implementation • ACL 2021 • Chenghao Yang, Yudong Zhang, Smaranda Muresan
Social media has become a valuable resource for the study of suicidal ideation and the assessment of suicide risk.
no code implementations • WS 2020 • Xiangyang Mou, Mo Yu, Bingsheng Yao, Chenghao Yang, Xiaoxiao Guo, Saloni Potdar, Hui Su
A lot of progress has been made to improve question answering (QA) in recent years, but the special problem of QA over narrative book stories has not been explored in-depth.
no code implementations • WS 2020 • Yuhui Zhang, Chenghao Yang, Zhengping Zhou, Zhiyuan Liu
While large-scale pretraining has achieved great success in many NLP tasks, it has not been fully studied whether external linguistic knowledge can improve data-driven models.
1 code implementation • ACL 2020 • Yuan Zang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Meng Zhang, Qun Liu, Maosong Sun
Also, further experiments show our model has higher transferability and can bring more robustness enhancement to victim models by adversarial training.
1 code implementation • ACL 2019 • Fanchao Qi, Jun-Jie Huang, Chenghao Yang, Zhiyuan Liu, Xiao Chen, Qun Liu, Maosong Sun
In this paper, we verify the effectiveness of sememes, the minimum semantic units of human languages, in modeling SC by a confirmatory experiment.
multi-word expression embedding multi-word expression sememe prediction
1 code implementation • 1 Jun 2019 • Junjie Huang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Maosong Sun
Word similarity computation is a widely recognized task in the field of lexical semantics.
1 code implementation • 28 Jan 2019 • Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Qiang Dong, Maosong Sun, Zhendong Dong
In this paper, we present an open sememe-based lexical knowledge base OpenHowNet.
1 code implementation • 31 Oct 2018 • Jing Yu, Chenghao Yang, Zengchang Qin, Zhuoqian Yang, Yue Hu, Yanbing Liu
A joint neural model is proposed to learn feature representation individually in each modality.
Multimedia