Natural language reasoning, a survey

F Yu, H Zhang, P Tiwari, B Wang - ACM Computing Surveys, 2024‏ - dl.acm.org
This survey article proposes a clearer view of Natural Language Reasoning (NLR) in the
field of Natural Language Processing (NLP), both conceptually and practically …

Prompt programming for large language models: Beyond the few-shot paradigm

L Reynolds, K McDonell - Extended abstracts of the 2021 CHI …, 2021‏ - dl.acm.org
Prevailing methods for map** large generative language models to supervised tasks may
fail to sufficiently probe models' novel capabilities. Using GPT-3 as a case study, we show …

Multi-hop question answering

V Mavi, A Jangra, A Jatowt - Foundations and Trends® in …, 2024‏ - nowpublishers.com
Abstract The task of Question Answering (QA) has attracted significant research interest for a
long time. Its relevance to language understanding and knowledge retrieval tasks, along …

Exploring question-specific rewards for generating deep questions

Y **e, L Pan, D Wang, MY Kan, Y Feng - arxiv preprint arxiv:2011.01102, 2020‏ - arxiv.org
Recent question generation (QG) approaches often utilize the sequence-to-sequence
framework (Seq2Seq) to optimize the log-likelihood of ground-truth questions using teacher …

AFS graph: Multidimensional axiomatic fuzzy set knowledge graph for open-domain question answering

Q Lang, X Liu, W Jia - IEEE Transactions on Neural Networks …, 2022‏ - ieeexplore.ieee.org
Open-domain question answering (QA) tasks require a model to retrieve inference chains
associated with the answer from massive documents. The core of a QA model is the …

Domain adaptation for subjective induction questions answering on products by adversarial disentangled learning

Y Zhang, J Yu, Y Rao, L Zheng, Q Su… - Proceedings of the …, 2024‏ - aclanthology.org
This paper focuses on answering subjective questions about products. Different from the
factoid question with a single answer span, this subjective one involves multiple viewpoints …

Few-shot question generation for personalized feedback in intelligent tutoring systems

D Kulshreshtha, M Shayan, R Belfer, S Reddy… - PAIS …, 2022‏ - ebooks.iospress.nl
Existing work on generating hints in Intelligent Tutoring Systems (ITS) focuses mostly on
manual and non-personalized feedback. In this work, we explore automatically generated …

Rtrl: Relation-aware transformer with reinforcement learning for deep question generation

H Zeng, B Wei, J Liu - Knowledge-Based Systems, 2024‏ - Elsevier
Deep question generation is an important yet challenging NLP task where a multi-step
reasoning chain connecting multiple documents is required to answer the questions. In this …

Entity guided question generation with contextual structure and sequence information capturing

Q Huang, M Fu, L Mo, Y Cai, J Xu, P Li, Q Li… - Proceedings of the …, 2021‏ - ojs.aaai.org
Question generation is a challenging task and has attracted widespread attention in recent
years. Although previous studies have made great progress, there are still two main …

Improving paragraph-level question generation with extended answer network and uncertainty-aware beam search

H Zeng, Z Zhi, J Liu, B Wei - Information Sciences, 2021‏ - Elsevier
Question Generation (QG), which aims to generate a question given the relevant context, is
essential to build conversational and question–answering systems. Existing neural question …