Search Results for author:
Found 9 papers, 5 papers with code
Learning to Generate Explanation from e-Hospital Services for Medical Suggestion
Explaining the reasoning of neural models has attracted attention in recent years.
E-QGen: Educational Lecture Abstract-based Question Generation System
To optimize the preparation process for educators in academic lectures and associated question-and-answer sessions, this paper presents E-QGen, a lecture abstract-based question generation system.
How We Refute Claims: Automatic Fact-Checking through Flaw Identification and Explanation
Automated fact-checking is a crucial task in the governance of internet content.
Three Questions Concerning the Use of Large Language Models to Facilitate Mathematics Learning
Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored.
RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training
Existing intent detection approaches have highly relied on adaptively pre-training language models with large-scale datasets, yet the predominant cost of data collection may hinder their superiority.
ZARA: Improving Few-Shot Self-Rationalization for Small Language Models
Inspired by the implicit mental process of how human beings assess explanations, we present a novel approach, Zero-shot Augmentation of Rationale-Answer pairs (ZARA), to automatically construct pseudo-parallel data for self-training by reducing the problem of plausibility judgement to natural language inference.
LED: A Dataset for Life Event Extraction from Dialogs
Our proposed life event dialog dataset and in-depth analysis of IE frameworks will facilitate future research on life event extraction from conversations.
Ten Questions in Lifelog Mining and Information Recall
With the advance of science and technology, people are used to record their daily life events via writing blogs, uploading social media posts, taking photos, or filming videos.
