no code implementations • 8 Oct 2024 • Lang Qin, Yao Zhang, Hongru Liang, Adam Jatowt, Zhenglu Yang
To address this issue, we propose MedPH, a Medical dialogue generation method for mitigating the problem of Patient Hallucinations designed to detect and cope with hallucinations.
1 code implementation • 7 Aug 2024 • Weihong Du, Jia Liu, Zujie Wen, dingnan jin, Hongru Liang, Wenqiang Lei
It is time-saving to build a reading assistant for customer service representations (CSRs) when reading user manuals, especially information-rich ones.
1 code implementation • 7 Aug 2024 • Weihong Du, Wenrui Liao, Hongru Liang, Wenqiang Lei
To this end, we propose a new benchmark PAGED, equipped with a large high-quality dataset and standard evaluations.
1 code implementation • 20 May 2024 • Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, dingnan jin, Hongru Liang, Tat-Seng Chua
To this end, we introduce CLAMBER, a benchmark for evaluating LLMs using a well-organized taxonomy.
no code implementations • 11 Mar 2024 • Tong Zhang, Chen Huang, Yang Deng, Hongru Liang, Jia Liu, Zujie Wen, Wenqiang Lei, Tat-Seng Chua
We investigate non-collaborative dialogue agents, which are expected to engage in strategic conversations with diverse users, for securing a mutual agreement that leans favorably towards the system's objectives.
1 code implementation • 11 Oct 2023 • Lang Qin, Yao Zhang, Hongru Liang, Jun Wang, Zhenglu Yang
Accurate knowledge selection is critical in knowledge-grounded dialogue systems.
1 code implementation • 9 Aug 2023 • Hongru Liang, Jingyao Liu, Yuanxin Xiang, Jiachen Du, Lanjun Zhou, Shushen Pan, Wenqiang Lei
Based on the observation that such missing information may already be presented in user comments, we propose to study the automated music labeling in an essential but under-explored setting, where the model is required to harvest more diverse and valid labels from the users' comments given limited gold labels.
1 code implementation • 7 Jun 2023 • Hongru Liang, Jia Liu, Weihong Du, dingnan jin, Wenqiang Lei, Zujie Wen, Jiancheng Lv
The machine reading comprehension (MRC) of user manuals has huge potential in customer service.
no code implementations • 7 Apr 2022 • Wenqiang Lei, Yao Zhang, Feifan Song, Hongru Liang, Jiaxin Mao, Jiancheng Lv, Zhenglu Yang, Tat-Seng Chua
To this end, we contribute to advance the study of the proactive dialogue policy to a more natural and challenging setting, i. e., interacting dynamically with users.
no code implementations • Findings (ACL) 2022 • Yao Zhang, Peiyao Li, Hongru Liang, Adam Jatowt, Zhenglu Yang
In the question answering(QA) task, multi-hop reasoning framework has been extensively studied in recent years to perform more efficient and interpretable answer reasoning on the Knowledge Graph(KG).
no code implementations • 24 May 2021 • Hongru Liang, Huaqing Li
Human evaluation is becoming a necessity to test the performance of Chatbots.
no code implementations • 23 Mar 2021 • Hongru Liang, Haozheng Wang, Qian Li, Jun Wang, Guandong Xu, Jiawei Chen, Jin-Mao Wei, Zhenglu Yang
Learning and analyzing rap lyrics is a significant basis for many web applications, such as music recommendation, automatic music categorization, and music information retrieval, due to the abundant source of digital music in the World Wide Web.
no code implementations • 22 Dec 2020 • Yao Zhang, Xu Zhang, Jun Wang, Hongru Liang, Wenqiang Lei, Zhe Sun, Adam Jatowt, Zhenglu Yang
The current methods for the link prediction taskhavetwonaturalproblems:1)the relation distributions in KGs are usually unbalanced, and 2) there are many unseen relations that occur in practical situations.
no code implementations • EMNLP 2021 • Yao Zhang, Hongru Liang, Adam Jatowt, Wenqiang Lei, Xin Wei, Ning Jiang, Zhenglu Yang
To the best of our knowledge, there lacks a general framework that approaches multi-hop reasoning in mixed long-short distance reasoning scenarios.
1 code implementation • COLING 2018 • Hongru Liang, Haozheng Wang, Jun Wang, ShaoDi You, Zhe Sun, Jin-Mao Wei, Zhenglu Yang
Learning social media content is the basis of many real-world applications, including information retrieval and recommendation systems, among others.