DIMSUM: Discourse in Mathematical Reasoning as a Supervision Module

Fuente: arXiv
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Hauptverfasser: Sharma, Krish, Barman, Niyar R, Chaturvedi, Akshay, Asher, Nicholas
Format: Preprint
Veröffentlicht: 2025
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author Sharma, Krish
Barman, Niyar R
Chaturvedi, Akshay
Asher, Nicholas
author_facet Sharma, Krish
Barman, Niyar R
Chaturvedi, Akshay
Asher, Nicholas
contents We look at reasoning on GSM8k, a dataset of short texts presenting primary school, math problems. We find, with Mirzadeh et al. (2024), that current LLM progress on the data set may not be explained by better reasoning but by exposure to a broader pretraining data distribution. We then introduce a novel information source for helping models with less data or inferior training reason better: discourse structure. We show that discourse structure improves performance for models like Llama2 13b by up to 160%. Even for models that have most likely memorized the data set, adding discourse structural information to the model still improves predictions and dramatically improves large model performance on out of distribution examples.
format Preprint
id arxiv_https___arxiv_org_abs_2503_04685
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle DIMSUM: Discourse in Mathematical Reasoning as a Supervision Module
Sharma, Krish
Barman, Niyar R
Chaturvedi, Akshay
Asher, Nicholas
Computation and Language
We look at reasoning on GSM8k, a dataset of short texts presenting primary school, math problems. We find, with Mirzadeh et al. (2024), that current LLM progress on the data set may not be explained by better reasoning but by exposure to a broader pretraining data distribution. We then introduce a novel information source for helping models with less data or inferior training reason better: discourse structure. We show that discourse structure improves performance for models like Llama2 13b by up to 160%. Even for models that have most likely memorized the data set, adding discourse structural information to the model still improves predictions and dramatically improves large model performance on out of distribution examples.
title DIMSUM: Discourse in Mathematical Reasoning as a Supervision Module
topic Computation and Language
url https://arxiv.org/abs/2503.04685