17 citations · 21 across the 10 of their papers we have counts for
10 papers
LANID: LLM-assisted New Intent Discovery
Lu Fan, Jiashu Pu, Rongsheng Zhang +1
Task-oriented Dialogue Systems (TODS) often face the challenge of encountering new intents. New Intent Discovery (NID) is a crucial task that aims to identify these novel intents w…
HoLLMwood: Unleashing the Creativity of Large Language Models in Screenwriting via Role Playing
Jing Chen, Xinyu Zhu, Cheng Yang +8
Generative AI has demonstrated unprecedented creativity in the field of computer vision, yet such phenomena have not been observed in natural language processing. In particular, la…
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation
Jiashu Pu, Yajing Wan, Yuru Zhang +6
Previous in-context learning (ICL) research has focused on tasks such as classification, machine translation, text2table, etc., while studies on whether ICL can improve human-like…
Examining the Effect of Pre-training on Time Series Classification
Jiashu Pu, Shiwei Zhao, Ling Cheng +4
Although the pre-training followed by fine-tuning paradigm is used extensively in many fields, there is still some controversy surrounding the impact of pre-training on the fine-tu…
Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics
Yongzhu Chang, Rongsheng Zhang, Lin Jiang +3
Lyrics generation is a well-known application in natural language generation research, with several previous studies focusing on generating accurate lyrics using precise control su…
I-WAS: a Data Augmentation Method with GPT-2 for Simile Detection
Yongzhu Chang, Rongsheng Zhang, Jiashu Pu
Simile detection is a valuable task for many natural language processing (NLP)-based applications, particularly in the field of literature. However, existing research on simile det…
Neighborhood-based Hard Negative Mining for Sequential Recommendation
Lu Fan, Jiashu Pu, Rongsheng Zhang +1
Negative sampling plays a crucial role in training successful sequential recommendation models. Instead of merely employing random negative sample selection, numerous strategies ha…
Probing Simile Knowledge from Pre-trained Language Models
Weijie Chen, Yongzhu Chang, Rongsheng Zhang +6
Simile interpretation (SI) and simile generation (SG) are challenging tasks for NLP because models require adequate world knowledge to produce predictions. Previous works have empl…
Dialog Intent Induction via Density-based Deep Clustering Ensemble
Jiashu Pu, Guandan Chen, Yongzhu Chang +1
Existing task-oriented chatbots heavily rely on spoken language understanding (SLU) systems to determine a user's utterance's intent and other key information for fulfilling specif…
Taming Repetition in Dialogue Generation
Yadong Xi, Jiashu Pu, Xiaoxi Mao
The wave of pre-training language models has been continuously improving the quality of the machine-generated conversations, however, some of the generated responses still suffer f…