10 citations · 29 across the 7 of their papers we have counts for
6 papers · 1 filter
LIONs: An Empirically Optimized Approach to Align Language Models
Xiao Yu, Qingyang Wu, Yu Li +1
Alignment is a crucial step to enhance the instruction-following and conversational abilities of language models. Despite many recent work proposing new algorithms, datasets, and t…
FaceChat: An Emotion-Aware Face-to-face Dialogue Framework
Deema Alnuhait, Qingyang Wu, Zhou Yu
While current dialogue systems like ChatGPT have made significant advancements in text-based interactions, they often overlook the potential of other modalities in enhancing the ov…
Perception Score, A Learned Metric for Open-ended Text Generation Evaluation
Jing Gu, Qingyang Wu, Zhou Yu
Automatic evaluation for open-ended natural language generation tasks remains a challenge. Existing metrics such as BLEU show a low correlation with human judgment. We propose a no…
On the Generation of Medical Dialogues for COVID-19
Wenmian Yang, Guangtao Zeng, Bowen Tan +9
Under the pandemic of COVID-19, people experiencing COVID19-related symptoms or exposed to risk factors have a pressing need to consult doctors. Due to hospital closure, a lot of c…
A Tailored Pre-Training Model for Task-Oriented Dialog Generation
Jing Gu, Qingyang Wu, Chongruo Wu +2
The recent success of large pre-trained language models such as BERT and GPT-2 has suggested the effectiveness of incorporating language priors in downstream dialog generation task…
Importance-Aware Learning for Neural Headline Editing
Qingyang Wu, Lei Li, Hao Zhou +2
Many social media news writers are not professionally trained. Therefore, social media platforms have to hire professional editors to adjust amateur headlines to attract more reade…