Mathematical Reasoning

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Most implemented papers

Analysing Mathematical Reasoning Abilities of Neural Models

deepmind/mathematics_dataset ICLR 2019

The structured nature of the mathematics domain, covering arithmetic, algebra, probability and calculus, enables the construction of training and test splits designed to clearly illuminate the capabilities and failure-modes of different architectures, as well as evaluate their ability to compose and relate knowledge and learned processes.

Compositional Generalization with Tree Stack Memory Units

ForoughA/recursiveMemNet 5 Nov 2019

We study compositional generalization, viz., the problem of zero-shot generalization to novel compositions of concepts in a domain.

Measuring Mathematical Problem Solving With the MATH Dataset

hendrycks/math 5 Mar 2021

To facilitate future research and increase accuracy on MATH, we also contribute a large auxiliary pretraining dataset which helps teach models the fundamentals of mathematics.

Training Verifiers to Solve Math Word Problems

openai/grade-school-math 27 Oct 2021

State-of-the-art language models can match human performance on many tasks, but they still struggle to robustly perform multi-step mathematical reasoning.

Learning to Prove Theorems via Interacting with Proof Assistants

princeton-vl/CoqGym 21 May 2019

Proof assistants offer a formalism that resembles human mathematical reasoning, representing theorems in higher-order logic and proofs as high-level tactics.

DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoV

flow-project/flow 3 Sep 2020

To this end, we propose a Decentralized Reinforcement Learning at the Edge for traffic light control in the IoV (DRLE).

Reverse Operation based Data Augmentation for Solving Math Word Problems

yiyunya/RODA 4 Oct 2020

Automatically solving math word problems is a critical task in the field of natural language processing.

Compositional Processing Emerges in Neural Networks Solving Math Problems

jlrussin/interpret-math-transformer 19 May 2021

A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition.

Reasoning with Transformer-based Models: Deep Learning, but Shallow Reasoning

dig-team/failbert AKBC 2021

Recent years have seen impressive performance of transformer-based models on different natural language processing tasks.

A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis

JohnnyYeeee/math_prog_synth_env 15 Jul 2021

We convert the DeepMind Mathematics Dataset into a reinforcement learning environment by interpreting it as a program synthesis problem.