• Home
  • Search
  • Towards Literate Artificial Intelligence
  • https://doi.org/10.1184/r1/11898378.v1Copy DOI Icon

Towards Literate Artificial Intelligence

Show More
  • Abstract
  • Literature Map
  • Similar Papers
Abstract

Standardized tests are used to test students as they progress in the formal education system. These tests are readily available and have clear evaluation procedures.Hence, it has been proposed that these tests can serve as good benchmarks for AI. In this thesis, we propose approaches for solving some common standardized teststaken by students such as reading comprehensions, elementary science exams, geometry questions in the SAT exam and mechanics questions in the AP physics exam.Answering these test problems requires deep linguistic (and sometimes visual) understanding and reasoning capabilities which is challenging for modern AI systems. In the first part of this thesis, we explore novel approaches to answer natural language comprehension tests such as reading comprehensions and elementary science tests (chapters 4, 5 and 6). These tests evaluate the system’s ability to understand text through a question-answering task. We present new latent structure models for these tasks. We posit that there is a hidden (latent) structure that explains the relation between the question, the correct answer, and the piece of text. We call this the answer-entailing structure; given the structure, the correctness of the answeris evident. Since the structure is latent, it must be inferred. We present a unified max-margin framework that learns to find these hidden structures given a corpus ofquestion-answer pairs, and uses what it learns to answer questions on novel texts. We also describe a simple but effective extension of this framework to incorporatemulti-task learning on the different subtasks that are required to perform the overall task (chapter 4), a deeper representation of language based on AMRs (chapter5) and how can we incorporate external knowledge in the answer-entailing structure (chapter 6). These advances help us obtain state-of-the-art performance on two well-known natural language comprehension benchmarks. In the second part of this thesis (chapter 7), we tackle some hard reasoning problems in the domains of math and science - geometry questions in the SAT exam and mechanics question in the AP physics exam. Solving these problems requires an ability to incorporate the rich domain knowledge as well as an ability to perform reasoning based on this knowledge. We propose a parsing to programs (P2P) approach for these problems. P2P assumes a formal representation language of the domain and domain knowledge written down as programs. This domain knowledge can be manually provided by a domain expert, or, as we show in our work, can be extracted by reading a number of textbooks in an automated way. When presentedwith a question, P2P learns a representation of the question in the formal language via a multi-modal semantic parser. Then, it uses the formal question interpretation and the domain knowledge to obtain an answer by using a probabilistic reasoner. A key bottleneck in building these models is the amount of domain-specific supervisionrequired to build them. Thus, in the final part of this thesis (chapter 8), we propose a self-training method based on curriculum learning that jointly learns to generate and answer questions. This method obtains near state-of-the-art models on a number of natural language comprehension tests with lesser supervision.

Similar Papers
  • Research Article
  • Citations1

STUDENTS’ READING-RELATED FACTORS AS PREDICTORS OF ACHIEVEMENT IN ENGLISH READING COMPREHENSION IN LAGELU LOCAL GOVERNMENT AREA, OYO STATE, NIGERIA

  • Dec 17, 2018
  • European Journal of Education Studies
  • Maxwell Olakunle Araromi +1
  • PDF
  • Conference Article
  • Citations29

Semantic Parsing for Textual Entailment

  • Jan 01, 2015
  • Elisabeth Lien +1
  • Research Article
  • Citations14

The Reading Strategies Used by EFL Technical Students

  • Dec 01, 2006
  • Shiu-Chen Hsu
  • Research Article

De-mystifying sign language acquisition and development in deaf children

  • Jul 20, 2017
  • Scientific Journal of Pure and Applied Sciences
  • Patrick Sibanda
  • Research Article

Keeleküsimus Õpetatud Eesti Seltsis

  • Dec 29, 2014
  • Ajakirjad. Journals by UT
  • Kersti Taal
  • Dissertation
  • Citations3

Factors Affecting Summary Writing and Their Impact on Reading Comprehension Assessment.

  • Jan 01, 1986
  • Martha Head
  • Research Article

Formal Languages, Formally and Coinductively

  • Sep 19, 2017
  • Logical Methods in Computer Science
  • Dmitriy Traytel
  • Research Article
  • Citations3

The Effects of DRA and DR-TA Methods on Students’ Reading Comprehension for State Islamic Senior High School

  • Mar 23, 2018
  • American Journal of Educational Research
  • Abdullah Hasan
  • Research Article
  • Citations3

Investigating the Role of Critical Reading Strategies in Developing Students’ Reading Comprehension

  • Jun 19, 2024
  • Journal of English Language Learning
  • Andini Putri Rahmasari +1
  • Research Article

Tool for evaluation using virtual reality

  • Nov 30, 2011
  • Journal of Engineering and Computer Innovations
  • Adriana Soares Pereira +1
  • Research Article

Improving Reading Comprehension Through Collaborative Strategic Reading

  • Sep 01, 2016
  • Jimmi Daniel
  • Research Article

Worchitect: An English Grammar (Parts of Speech) Card Game

  • Jun 04, 2018
  • Adi Idham Jailani +4
  • Research Article
  • Citations3

Recipe formal definition language for operating procedures synthesis

  • Aug 01, 2004
  • Computers & Chemical Engineering
  • H Gabbar
  • Supplementary Content

Learning and teaching languages in technology-mediated environments : why modes and meaning making matter

  • Feb 27, 2019
  • Open Research Online (The Open University)
  • Mirjam Hauck
  • Research Article

Fast mapping in adults with DLD (McGregor et al., 2020)

  • Aug 13, 2020
  • Figshare
  • Karla K Mcgregor +3
Cactus Communications logo

Copyright 2026 Cactus Communications. All rights reserved.