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Found 6 papers, 4 papers with code
Multi-Operational Mathematical Derivations in Latent Space
To this end, we introduce different multi-operational representation paradigms, modelling mathematical operations as explicit geometric transformations.
Generating Mathematical Derivations with Large Language Models
In addition, we analyse 1. 7K equations, and over 200 derivations, to highlight common reasoning errors such as the inclusion of incorrect, irrelevant, and redundant equations.
A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers
This paper proposes a methodology for generating and perturbing detailed derivations of equations at scale, aided by a symbolic engine, to evaluate the generalisability of Transformers to out-of-distribution mathematical reasoning problems.
A Survey in Mathematical Language Processing
Informal mathematical text underpins real-world quantitative reasoning and communication.
PhysNLU: A Language Resource for Evaluating Natural Language Understanding and Explanation Coherence in Physics
In order for language models to aid physics research, they must first encode representations of mathematical and natural language discourse which lead to coherent explanations, with correct ordering and relevance of statements.
Similarity-Based Equational Inference in Physics
Automating the derivation of published results is a challenge, in part due to the informal use of mathematics by physicists, compared to that of mathematicians.
