23 citations · 51 across the 12 of their papers we have counts for
7 papers · 1 filter
SCOP: Evaluating the Comprehension Process of Large Language Models from a Cognitive View
Yongjie Xiao, Hongru Liang, Peixin Qin +2
Despite the great potential of large language models(LLMs) in machine comprehension, it is still disturbing to fully count on them in real-world scenarios. This is probably because…
Listening to Patients: A Framework of Detecting and Mitigating Patient Misreport for Medical Dialogue Generation
Lang Qin, Yao Zhang, Hongru Liang +2
Medical Dialogue Systems aim to provide automated healthcare support through patient-agent conversations. Previous efforts typically regard patients as ideal users -- one who accur…
Well Begun is Half Done: Generator-agnostic Knowledge Pre-Selection for Knowledge-Grounded Dialogue
Lang Qin, Yao Zhang, Hongru Liang +2
Accurate knowledge selection is critical in knowledge-grounded dialogue systems. Towards a closer look at it, we offer a novel perspective to organize existing literature, i.e., kn…
Knowing-how & Knowing-that: A New Task for Machine Comprehension of User Manuals
Hongru Liang, Jia Liu, Weihong Du +4
The machine reading comprehension (MRC) of user manuals has huge potential in customer service. However, current methods have trouble answering complex questions. Therefore, we int…
Towards Standard Criteria for human evaluation of Chatbots: A Survey
Hongru Liang, Huaqing Li
Human evaluation is becoming a necessity to test the performance of Chatbots. However, off-the-shelf settings suffer the severe reliability and replication issues partly because of…
A General Framework for Learning Prosodic-Enhanced Representation of Rap Lyrics
Hongru Liang, Haozheng Wang, Qian Li +5
Learning and analyzing rap lyrics is a significant basis for many web applications, such as music recommendation, automatic music categorization, and music information retrieval, d…
JTAV: Jointly Learning Social Media Content Representation by Fusing Textual, Acoustic, and Visual Features
Hongru Liang, Haozheng Wang, Jun Wang +4
Learning social media content is the basis of many real-world applications, including information retrieval and recommendation systems, among others. In contrast with previous work…