1 code implementation • Findings (EMNLP) 2021 • Kexin Wang, Nils Reimers, Iryna Gurevych
Learning sentence embeddings often requires a large amount of labeled data.
1 code implementation • 9 Jan 2024 • Jiaan Wang, Jianfeng Qu, Kexin Wang, Zhixu Li, Wen Hua, Ximing Li, An Liu
Knowledge-grounded dialogue (KGD) learns to generate an informative response based on a given dialogue context and external knowledge (\emph{e. g.}, knowledge graphs; KGs).
1 code implementation • 31 Dec 2023 • Licai Sun, Zheng Lian, Kexin Wang, Yu He, Mingyu Xu, Haiyang Sun, Bin Liu, JianHua Tao
Video-based facial affect analysis has recently attracted increasing attention owing to its critical role in human-computer interaction.
Ranked #3 on Dynamic Facial Expression Recognition on FERV39k
Dynamic Facial Expression Recognition Emotion Recognition +2
no code implementations • 21 Nov 2023 • Yuxi Heluo, Kexin Wang, Charles W. Robson
In this work, we contribute the first visual open-source empirical study on human behaviour during the COVID-19 pandemic, in order to investigate how compliant a general population is to mask-wearing-related public-health policy.
1 code implementation • 1 Nov 2023 • Yongxin Huang, Kexin Wang, Sourav Dutta, Raj Nath Patel, Goran Glavaš, Iryna Gurevych
As a solution, we propose AdaSent, which decouples SEPT from DAPT by training a SEPT adapter on the base PLM.
1 code implementation • 19 Jul 2023 • Nandan Thakur, Kexin Wang, Iryna Gurevych, Jimmy Lin
In this work, we provide SPRINT, a unified Python toolkit based on Pyserini and Lucene, supporting a common interface for evaluating neural sparse retrieval.
no code implementations • 18 Jun 2023 • Kexin Wang, Yunlong Zhao, Qianqian Dong, Tom Ko, Mingxuan Wang
And our framework also surpasses the strong baseline in ranking accuracy on each fine-grained segment.
no code implementations • 5 Jun 2023 • Qianqian Dong, Zhiying Huang, Qiao Tian, Chen Xu, Tom Ko, Yunlong Zhao, Siyuan Feng, Tang Li, Kexin Wang, Xuxin Cheng, Fengpeng Yue, Ye Bai, Xi Chen, Lu Lu, Zejun Ma, Yuping Wang, Mingxuan Wang, Yuxuan Wang
For the speech synthesis part, we adopt the existing VALL-E X approach and build a unit-based audio language model.
2 code implementations • 23 May 2023 • Kexin Wang, Nils Reimers, Iryna Gurevych
This drives us to build a benchmark for this task including multiple datasets from heterogeneous domains.
3 code implementations • 18 Apr 2023 • Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen, Mingyu Xu, Kexin Wang, Ke Xu, Yu He, Ying Li, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, JianHua Tao
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
1 code implementation • 31 Mar 2023 • Haritz Puerto, Tim Baumgärtner, Rachneet Sachdeva, Haishuo Fang, Hao Zhang, Sewin Tariverdian, Kexin Wang, Iryna Gurevych
To ease research in multi-agent models, we extend UKP-SQuARE, an online platform for QA research, to support three families of multi-agent systems: i) agent selection, ii) early-fusion of agents, and iii) late-fusion of agents.
no code implementations • 14 Nov 2022 • Anxo Pérez, Neha Warikoo, Kexin Wang, Javier Parapar, Iryna Gurevych
Depressive disorders constitute a severe public health issue worldwide.
1 code implementation • 19 Aug 2022 • Rachneet Sachdeva, Haritz Puerto, Tim Baumgärtner, Sewin Tariverdian, Hao Zhang, Kexin Wang, Hossain Shaikh Saadi, Leonardo F. R. Ribeiro, Iryna Gurevych
In this paper, we introduce SQuARE v2, the new version of SQuARE, to provide an explainability infrastructure for comparing models based on methods such as saliency maps and graph-based explanations.
1 code implementation • 17 Jul 2022 • Kexin Wang, Zhixu Li, Jiaan Wang, Jianfeng Qu, Ying He, An Liu, Lei Zhao
Nevertheless, the correlations between knowledge implied in the multi-turn context and the transition regularities between relations in KGs are under-explored.
1 code implementation • ACL 2022 • Tim Baumgärtner, Kexin Wang, Rachneet Sachdeva, Max Eichler, Gregor Geigle, Clifton Poth, Hannah Sterz, Haritz Puerto, Leonardo F. R. Ribeiro, Jonas Pfeiffer, Nils Reimers, Gözde Gül Şahin, Iryna Gurevych
Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e. g., extractive, abstractive), require different model architectures (e. g., generative, discriminative), and setups (e. g., with or without retrieval).
5 code implementations • NAACL 2022 • Kexin Wang, Nandan Thakur, Nils Reimers, Iryna Gurevych
This limits the usage of dense retrieval approaches to only a few domains with large training datasets.
Ranked #9 on Zero-shot Text Search on BEIR
6 code implementations • 14 Apr 2021 • Kexin Wang, Nils Reimers, Iryna Gurevych
Learning sentence embeddings often requires a large amount of labeled data.
Ranked #1 on Re-Ranking on AskUbuntu
no code implementations • 4 Mar 2021 • Shuangyong Song, Kexin Wang, Chao Wang, Haiqing Chen, Huan Chen
In response generation task, proper sentimental expressions can obviously improve the human-like level of the responses.
no code implementations • 25 Jun 2020 • Yuzhu Guo, Kang Pan, Simeng Li, Zongchang Han, Kexin Wang, Li Li
Autoencoders have been widely used for dimensional reduction and feature extraction.
no code implementations • 1 Jul 2019 • Kexin Wang, Yu Zhou, Shaonan Wang, Jiajun Zhang, Cheng-qing Zong
Recent work has shown that memory modules are crucial for the generalization ability of neural networks on learning simple algorithms.