1 code implementation • 6 Feb 2025 • Chenyang Huang, Hao Zhou, Cameron Jen, Kangjie Zheng, Osmar R. Zaïane, Lili Mou
Length-control summarization aims to condense long texts into a short one within a certain length limit.
1 code implementation • 6 Feb 2025 • Chenyang Huang, Fei Huang, Zaixiang Zheng, Osmar R. Zaïane, Hao Zhou, Lili Mou
To this end, we propose an M-DAT approach to non-autoregressive multilingual machine translation.
1 code implementation • 4 Jun 2024 • Chenyang Huang, Abbas Ghaddar, Ivan Kobyzev, Mehdi Rezagholizadeh, Osmar R. Zaiane, Boxing Chen
In this work, we introduce OTTAWA, a novel Optimal Transport (OT)-based word aligner specifically designed to enhance the detection of hallucinations and omissions in MT systems.
no code implementations • 17 Apr 2024 • Mohammad Khosravani, Chenyang Huang, Amine Trabelsi
This paper introduces a novel extractive approach for key point generation, that outperforms previous state-of-the-art methods for the task.
no code implementations • 29 Feb 2024 • Yuqiao Wen, Behzad Shayegh, Chenyang Huang, Yanshuai Cao, Lili Mou
The ability of zero-shot translation emerges when we train a multilingual model with certain translation directions; the model can then directly translate in unseen directions.
1 code implementation • ACL 2022 • Puyuan Liu, Chenyang Huang, Lili Mou
Text summarization aims to generate a short summary for an input text.
no code implementations • 16 May 2022 • Qiao Xiang, Ridi Wen, Chenyang Huang, Yuxin Wang, Franck Le
Data plane verification (DPV) is important for finding network errors.
2 code implementations • 14 Oct 2021 • Chenyang Huang, Hao Zhou, Osmar R. Zaïane, Lili Mou, Lei LI
How do we perform efficient inference while retaining high translation quality?
no code implementations • 22 Sep 2021 • Chengzhang Dong, Chenyang Huang, Osmar Zaïane, Lili Mou
Explicitly modeling emotions in dialogue generation has important applications, such as building empathetic personal companions.
no code implementations • ACL (spnlp) 2021 • Chenyang Huang, Wei Yang, Yanshuai Cao, Osmar Zaïane, Lili Mou
In this paper, we propose a globally normalized model for context-free grammar (CFG)-based semantic parsing.
no code implementations • NAACL 2021 • Chenyang Huang, Amine Trabelsi, Xuebin Qin, Nawshad Farruque, Lili Mou, Osmar Za{\"\i}ane
Multi-label emotion classification is an important task in NLP and is essential to many applications.
no code implementations • 26 May 2021 • Nawshad Farruque, Chenyang Huang, Osmar Zaiane, Randy Goebel
In this paper, we present empirical analysis on basic and depression specific multi-emotion mining in Tweets with the help of state of the art multi-label classifiers.
5 code implementations • 12 Jan 2021 • Xuebin Qin, Deng-Ping Fan, Chenyang Huang, Cyril Diagne, Zichen Zhang, Adrià Cabeza Sant'Anna, Albert Suàrez, Martin Jagersand, Ling Shao
In this paper, we propose a simple yet powerful Boundary-Aware Segmentation Network (BASNet), which comprises a predict-refine architecture and a hybrid loss, for highly accurate image segmentation.
1 code implementation • ACL 2021 • Peng Xu, Dhruv Kumar, Wei Yang, Wenjie Zi, Keyi Tang, Chenyang Huang, Jackie Chi Kit Cheung, Simon J. D. Prince, Yanshuai Cao
This work shows that this does not always need to be the case: with proper initialization and optimization, the benefits of very deep transformers can carry over to challenging tasks with small datasets, including Text-to-SQL semantic parsing and logical reading comprehension.
1 code implementation • SEMEVAL 2020 • Anandh Perumal, Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane
In order to generate more meaningful explanations, we propose UNION, a unified end-to-end framework, to utilize several existing commonsense datasets so that it allows a model to learn more dynamics under the scope of commonsense reasoning.
29 code implementations • 18 May 2020 • Xuebin Qin, Zichen Zhang, Chenyang Huang, Masood Dehghan, Osmar R. Zaiane, Martin Jagersand
In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).
Ranked #1 on
Salient Object Detection
on SOD
no code implementations • 6 Nov 2019 • Chenyang Huang, Amine Trabelsi, Xuebin Qin, Nawshad Farruque, Osmar R. Zaïane
Most of the existing methods treat this task as a problem of single-label multi-class text classification.
1 code implementation • SEMEVAL 2019 • Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane
This paper describes the system submitted by ANA Team for the SemEval-2019 Task 3: EmoContext.
Ranked #3 on
Emotion Recognition in Conversation
on EC
Emotion Recognition in Conversation
General Classification
+2
no code implementations • 15 Nov 2018 • Chenyang Huang, Osmar R. Zaïane
Neural network-based Open-ended conversational agents automatically generate responses based on predictive models learned from a large number of pairs of utterances.
1 code implementation • NAACL 2018 • Chenyang Huang, Osmar Za{\"\i}ane, Amine Trabelsi, Nouha Dziri
Despite myriad efforts in the literature designing neural dialogue generation systems in recent years, very few consider putting restrictions on the response itself.