Computer Solution of Calculus Word Problems

By Eugene Charniak. 1969

Subfields: Natural Language Processing, Question Answering & Reading Comprehension

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Citations in the corpus

Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning. (2021, background): “(Bobrow, 1964; Charniak, 1969; Shi et al., 2015; Ling et al., 2017; Amini et al., 2019; Parisotto et al., 2016; Wang et al., 2018; Zou and Lu, 2019) as well as datasets (Ling et al.”
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms (2019, background): “…Features Due to sparsity of suitable data, early work on math word problem solving used pattern-matching to map word problems to mathematical expressions (Bo-brow, 1964; Charniak, 1968, 1969), as well as non-neural statistical modeling and semantic parsing approaches (Liguda and Pfeiffer, 2012).”
Deep Neural Solver for Math Word Problems (2017, methodology): “A similar approach is also used to solve English rate problems Charniak (1968, 1969).”
How well do Computers Solve Math Word Problems? Large-Scale Dataset Construction and Evaluation (2016, background): “In symbolic approaches (Bobrow, 1964a; Bobrow, 1964b; Charniak, 1968; Charniak, 1969; Bakman, 2007; Liguda and Pfeiffer, 2012; Shi et al., 2015), math problem sentences are transformed to certain structures (usually trees) by pattern matching, verb categorization, or semantic parsing.”
Automatically Solving Number Word Problems by Semantic Parsing and Reasoning (2015, methodology): “CARPS (Charniak, 1968, 1969) uses a similar approach to solve English rate problems.”
TM-generation model: a template-based method for automatically solving mathematical word problems (2021, background): “Researchers have attempted to address the task of automatic mathematical word problem solving since the 1960s [2, 3].”
Learning Fine-Grained Expressions to Solve Math Word Problems (2017, unknown): “Automatic math word problem solving meth-ods (Bobrow, 1964a,b; Charniak, 1968, 1969; Bri-ars and Larkin, 1984; Fletcher, 1985; Dellarosa, 1986; Bakman, 2007; Yuhui et al., 2010) developed before 2008 are mostly rule-based.”
The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers (2018, background): “Designing an automatic solver for mathematical word problems (MWPs) has a long history dated back to the 1960 s [1], [2], [3], and continues to attract intensive research attention.”
Understanding natural language (1972, background): “Although they may have very sophisticated mechanisms for using this information (as in CARPS (Charniak, 1969), which can solve word problems in calculus ) , they are each built for a special purpose, and do not handle information with the flexibility which would allow them to be adapted to other use”
A review of methods for automatic understanding of natural language mathematical problems (2008, unknown): “The program, CARPS i.e. Calculus Rate Problem Solver (Simmons 1970; Charniak 1968, 1969) written by Eugene Charniak reads, understands and solves rate problems stated in English.”
A Bottom-Up DAG Structure Extraction Model for Math Word Problems (2021, background): “Research on automatically solving MWP has a long history back to the 1960s (Charniak 1969).”