52 citations · 61 across the 10 of their papers we have counts for
6 papers · 1 filter
CoF-CoT: Enhancing Large Language Models with Coarse-to-Fine Chain-of-Thought Prompting for Multi-domain NLU Tasks
Hoang H. Nguyen, Ye Liu, Chenwei Zhang +2
While Chain-of-Thought prompting is popular in reasoning tasks, its application to Large Language Models (LLMs) in Natural Language Understanding (NLU) is under-explored. Motivated…
L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models
Ansong Ni, Pengcheng Yin, Yilun Zhao +11
Recently, large language models (LLMs), especially those that are pretrained on code, have demonstrated strong capabilities in generating programs from natural language inputs in a…
Investigating Answerability of LLMs for Long-Form Question Answering
Meghana Moorthy Bhat, Rui Meng, Ye Liu +2
As we embark on a new era of LLMs, it becomes increasingly crucial to understand their capabilities, limitations, and differences. Toward making further progress in this direction,…
ConceptNet infused DialoGPT for Underlying Commonsense Understanding and Reasoning in Dialogue Response Generation
Ye Liu, Wolfgang Maier, Wolfgang Minker +1
The pre-trained conversational models still fail to capture the implicit commonsense (CS) knowledge hidden in the dialogue interaction, even though they were pre-trained with an en…
Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots
Wenting Zhao, Ye Liu, Yao Wan +1
Few-shot table-to-text generation is a task of composing fluent and faithful sentences to convey table content using limited data. Despite many efforts having been made towards gen…
Empathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge
Ye Liu, Wolfgang Maier, Wolfgang Minker +1
One challenge for dialogue agents is to recognize feelings of the conversation partner and respond accordingly. In this work, RoBERTa-GPT2 is proposed for empathetic dialogue gener…