| Challenge: | Experimental results show that the proposed approach understands the meaning of each quantity in the text more. |
| Approach: | They propose a meaning-based approach for solving English math word problems . they analyze text, transform body and question parts into corresponding logic forms . Statistical models are proposed to select operator and operands . |
| Outcome: | The proposed approach outperforms existing systems on benchmark and noisy datasets. |
Similar Papers
Semantically-Aligned Universal Tree-Structured Solver for Math Word Problems (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing models focus on one-unknown linear MWPs. |
| Approach: | They propose a universal expression tree-structured solver that integrates multiple expression trees underlying a MWP into a single expression tree. |
| Outcome: | The proposed method outperforms state-of-the-art models on a MWPs dataset and generates a universal expression tree explicitly by deciding which symbol to generate . |
Math Word Problem Solving by Generating Linguistic Variants of Problem Statements (2023.acl-srw)
Copied to clipboard
Syed Rifat Raiyan, Md Nafis Faiyaz, Shah Md. Jawad Kabir, Mohsinul Kabir, Hasan Mahmud, Md Kamrul Hasan
| Challenge: | Existing models for solving Math Word Problems depend on shallow heuristics and spurious correlations to derive the solution expressions. |
| Approach: | They propose a framework for MWP solvers based on generation of linguistic variants of problem text. |
| Outcome: | The proposed framework improves the mathematical reasoning and robustness of the proposed model. |
Semantically-Aligned Equation Generation for Solving and Reasoning Math Word Problems (N19-1)
Copied to clipboard
| Challenge: | Existing methods to solve math word problems require accurate natural language understanding to bridge texts and math expressions. |
| Approach: | They propose a neural approach to automatically solve math word problems by operating symbols according to their semantic meanings in texts. |
| Outcome: | The proposed model outperforms state-of-the-art models and the best non-retrieval-based models over 10% accuracy in a Math23K dataset. |
Compositional Mathematical Encoding for Math Word Problems (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing MWP encoders work in a unimodal setting and map problem description to latent representation, then for decoding. |
| Approach: | They propose a Compositional Math Word Problem Solver which maps problem description to latent representation and decodes it in an interactive way. |
| Outcome: | Extensive experiments show that the proposed model outperforms state-of-the-art models on public benchmarks. |
Disentangling Text and Math in Word Problems: Evidence for the Bidimensional Structure of Large Language Models’ Reasoning (2025.findings-acl)
Copied to clipboard
Pedro Calais, Gabriel Franco, Zilu Tang, Themistoklis Nikas, Wagner Meira Jr., Evimaria Terzi, Mark Crovella
| Challenge: | Existing studies show that LLMs struggle with text interpretation and equation solving, despite distinct proficiencies in textual and mathematical components. |
| Approach: | They disentangle textual interpretation and mathematical solving steps in word problems drawn from Brazil's largest college entrance exam and popular grade school-level benchmark GSM8K. |
| Outcome: | The proposed model outperforms LLMs in Brazil's largest college entrance exam and popular grade school-level benchmark. |
Textual Enhanced Contrastive Learning for Solving Math Word Problems (2022.findings-emnlp)
Copied to clipboard
| Challenge: | Recent studies show that current models rely on shallow heuristics to predict solutions . a textual Enhanced Contrastive Learning framework enforces the models to distinguish semantically similar examples while holding different mathematical logic. |
| Approach: | They propose a textual Enhanced Contrastive Learning framework which enforces models to distinguish semantically similar examples while holding different mathematical logic. |
| Outcome: | The proposed framework improves on benchmark and challenge datasets in English and Chinese. |
A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers (2020.acl-main)
Copied to clipboard
| Challenge: | Existing MWP corpora are limited in language patterns and problem types . a new corpus of 2,305 MWps is proposed that is more diverse in terms of lexicon usage . |
| Approach: | They propose to use ASDiv to measure lexicon usage diversity of a given MWP corpus. |
| Outcome: | The proposed corpus covers more problem types and text patterns than existing corpora and reflects the true capability of solvers more faithfully. |
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints (2021.emnlp-main)
Copied to clipboard
| Challenge: | Existing approaches to generate arithmetic math word problems are invalid or have unsatisfactory language quality. |
| Approach: | They propose a method for automatically generating arithmetic math word problems from equations and context. |
| Outcome: | The proposed approach improves language quality and mathematical validity on three real-world MWP datasets. |
Math Word Problem Solving with Explicit Numerical Values (2021.acl-long)
Copied to clipboard
| Challenge: | Existing methods for solving math word problems ignore numerical values in solving problems. |
| Approach: | They propose a numerically-based approach that explicitly incorporates numerical values into a sequence-to-tree network and uses a mathematical properties prediction mechanism to capture category and comparison information of numerals. |
| Outcome: | The proposed model outperforms existing state-of-the-art models on the Math23K and APE datasets. |
Noun-MWP: Math Word Problems Meet Noun Answers (2022.coling-1)
Copied to clipboard
| Challenge: | Existing MWP solvers can handle Noun-MWPs, but they are not as efficient as other models. |
| Approach: | They propose a method to empower existing MWP solvers to handle Noun-MWPs. |
| Outcome: | The proposed model solves Noun-MWPs significantly better than other models and solves conventional MWP problems as well. |