Log In Sign Up

SMART: A Situation Model for Algebra Story Problems via Attributed Grammar

by   Yining Hong, et al.

Solving algebra story problems remains a challenging task in artificial intelligence, which requires a detailed understanding of real-world situations and a strong mathematical reasoning capability. Previous neural solvers of math word problems directly translate problem texts into equations, lacking an explicit interpretation of the situations, and often fail to handle more sophisticated situations. To address such limits of neural solvers, we introduce the concept of a situation model, which originates from psychology studies to represent the mental states of humans in problem-solving, and propose SMART, which adopts attributed grammar as the representation of situation models for algebra story problems. Specifically, we first train an information extraction module to extract nodes, attributes, and relations from problem texts and then generate a parse graph based on a pre-defined attributed grammar. An iterative learning strategy is also proposed to improve the performance of SMART further. To rigorously study this task, we carefully curate a new dataset named ASP6.6k. Experimental results on ASP6.6k show that the proposed model outperforms all previous neural solvers by a large margin while preserving much better interpretability. To test these models' generalization capability, we also design an out-of-distribution (OOD) evaluation, in which problems are more complex than those in the training set. Our model exceeds state-of-the-art models by 17% in the OOD evaluation, demonstrating its superior generalization ability.


page 1

page 2

page 3

page 4


Discriminative Sentence Modeling for Story Ending Prediction

Story Ending Prediction is a task that needs to select an appropriate en...

Deep Learning on Attributed Sequences

Recent research in feature learning has been extended to sequence data, ...

Narrative Modeling with Memory Chains and Semantic Supervision

Story comprehension requires a deep semantic understanding of the narrat...

Attributed Rhetorical Structure Grammar for Domain Text Summarization

This paper presents a new approach of automatic text summarization which...

StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts

Inferring spatial relations in natural language is a crucial ability an ...

TrUMAn: Trope Understanding in Movies and Animations

Understanding and comprehending video content is crucial for many real-w...

(Genetically) Improving Novelty in Procedural Story Generation

Procedural story generation (PCG) tailors a unique narrative experience ...