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This paper explores the task of answer-aware questions generation. Based on the attention-based pointer generator model, we propose to incorporate an auxiliary task of language modeling to help question generation in a hierarchical…

计算与语言 · 计算机科学 2019-09-02 Wenjie Zhou , Minghua Zhang , Yunfang Wu

Question Generation (QG), the task of automatically generating questions from a source input, has seen significant progress in recent years. Difficulty-controllable QG (DCQG) enables control over the difficulty level of generated questions…

计算与语言 · 计算机科学 2025-06-10 Bernardo Leite , Henrique Lopes Cardoso

Large pre-trained language models (LMs) have been shown to perform surprisingly well when fine-tuned on tasks that require commonsense and world knowledge. However, in end-to-end architectures, it is difficult to explain what is the…

计算与语言 · 计算机科学 2020-04-14 Veronica Latcinnik , Jonathan Berant

Qualitative relationships describe how increasing or decreasing one property (e.g. altitude) affects another (e.g. temperature). They are an important aspect of natural language question answering and are crucial for building chatbots or…

计算与语言 · 计算机科学 2019-08-13 Arindam Mitra , Chitta Baral , Aurgho Bhattacharjee , Ishan Shrivastava

We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers. We show how to train the model using a combination of supervised and reinforcement learning. After teacher forcing for…

This paper explores the task of Difficulty-Controllable Question Generation (DCQG), which aims at generating questions with required difficulty levels. Previous research on this task mainly defines the difficulty of a question as whether it…

计算与语言 · 计算机科学 2021-05-26 Yi Cheng , Siyao Li , Bang Liu , Ruihui Zhao , Sujian Li , Chenghua Lin , Yefeng Zheng

Recent advances in QA pair generation (QAG) have raised interest in applying this technique to the educational field. However, the diversity of QA types remains a challenge despite its contributions to comprehensive learning and assessment…

计算与语言 · 计算机科学 2023-06-13 Sugyeong Eo , Hyeonseok Moon , Jinsung Kim , Yuna Hur , Jeongwook Kim , Songeun Lee , Changwoo Chun , Sungsoo Park , Heuiseok Lim

The neural seq2seq based question generation (QG) is prone to generating generic and undiversified questions that are poorly relevant to the given passage and target answer. In this paper, we propose two methods to address the issue. (1) By…

计算与语言 · 计算机科学 2019-10-09 Jiazuo Qiu , Deyi Xiong

In this paper, we describe a system to rank suspected answers to natural language questions. We process both corpus and query using a new technique, predictive annotation, which augments phrases in texts with labels anticipating their being…

计算与语言 · 计算机科学 2007-05-23 Dragomir R. Radev , John Prager , Valerie Samn

The use of question-based activities (QBAs) is wide-spread in education, traditionally forming an integral part of the learning and assessment process. In this paper, we design and evaluate an automated question generation tool for…

Controllable text generation (CTG) by large language models has a huge potential to transform education for teachers and students alike. Specifically, high quality and diverse question generation can dramatically reduce the load on teachers…

计算与语言 · 计算机科学 2023-04-14 Sabina Elkins , Ekaterina Kochmar , Jackie C. K. Cheung , Iulian Serban

The task of Critical Questions Generation (CQs-Gen) aims to foster critical thinking by enabling systems to generate questions that expose underlying assumptions and challenge the validity of argumentative reasoning structures. Despite…

计算与语言 · 计算机科学 2025-09-24 Banca Calvo Figueras , Rodrigo Agerri

Automatic question generation can benefit many applications ranging from dialogue systems to reading comprehension. While questions are often asked with respect to long documents, there are many challenges with modeling such long documents.…

计算与语言 · 计算机科学 2019-10-24 Luu Anh Tuan , Darsh J Shah , Regina Barzilay

Verifying fact-checking claims poses a significant challenge, even for humans. Recent approaches have demonstrated that decomposing claims into relevant questions to gather evidence enhances the efficiency of the fact-checking process. In…

计算与语言 · 计算机科学 2024-08-02 Ritvik Setty , Vinay Setty

Large Language Models (LLMs) have in recent years demonstrated impressive prowess in natural language generation. A common practice to improve generation diversity is to sample multiple outputs from the model. However, there lacks a simple…

New systems employ Machine Learning to sift through large knowledge sources, creating flexible Large Language Models. These models discern context and predict sequential information in various communication forms. Generative AI, leveraging…

人工智能 · 计算机科学 2023-07-19 Ted Selker

Question Generation (QG) is the task of generating a plausible question for a given <passage, answer> pair. Template-based QG uses linguistically-informed heuristics to transform declarative sentences into interrogatives, whereas supervised…

计算与语言 · 计算机科学 2021-09-17 Chenyang Lyu , Lifeng Shang , Yvette Graham , Jennifer Foster , Xin Jiang , Qun Liu

Question generation (QG) is a natural language processing task with an abundance of potential benefits and use cases in the educational domain. In order for this potential to be realized, QG systems must be designed and validated with…

计算与语言 · 计算机科学 2025-11-05 Sabina Elkins , Ekaterina Kochmar , Jackie C. K. Cheung , Iulian Serban

Question generation (QG) is a natural language generation task where a model is trained to ask questions corresponding to some input text. Most recent approaches frame QG as a sequence-to-sequence problem and rely on additional features and…

计算与语言 · 计算机科学 2021-08-16 Luis Enrico Lopez , Diane Kathryn Cruz , Jan Christian Blaise Cruz , Charibeth Cheng

Inquisitive questions -- open-ended, curiosity-driven questions people ask as they read -- are an integral part of discourse processing (Kehler and Rohde, 2017; Onea, 2016) and comprehension (Prince, 2004). Recent work in NLP has taken…

计算与语言 · 计算机科学 2024-10-04 Yating Wu , Ritika Mangla , Alexandros G. Dimakis , Greg Durrett , Junyi Jessy Li