25 citations · 44 across the 5 of their papers we have counts for
6 papers · 1 filter
MathChat: Converse to Tackle Challenging Math Problems with LLM Agents
Yiran Wu, Feiran Jia, Shaokun Zhang +7
Employing Large Language Models (LLMs) to address mathematical problems is an intriguing research endeavor, considering the abundance of math problems expressed in natural language…
CodeT5+: Open Code Large Language Models for Code Understanding and Generation
Yue Wang, Hung Le, Akhilesh Deepak Gotmare +3
Large language models (LLMs) pretrained on vast source code have achieved prominent progress in code intelligence. However, existing code LLMs have two main limitations in terms of…
Machine Translation Verbosity Control for Automatic Dubbing
Surafel M. Lakew, Marcello Federico, Yue Wang +4
Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language. The task implies many challenges, one of which is gener…
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Yue Wang, Weishi Wang, Shafiq Joty +1
Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-rela…
Topic-Aware Neural Keyphrase Generation for Social Media Language
Yue Wang, Jing Li, Hou Pong Chan +3
A huge volume of user-generated content is daily produced on social media. To facilitate automatic language understanding, we study keyphrase prediction, distilling salient informa…
Microblog Hashtag Generation via Encoding Conversation Contexts
Yue Wang, Jing Li, Irwin King +2
Automatic hashtag annotation plays an important role in content understanding for microblog posts. To date, progress made in this field has been restricted to phrase selection from…