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Found 5 papers, 4 papers with code
Continual Pre-training of Language Models for Math Problem Understanding with Syntax-Aware Memory Network
In this paper, we study how to continually pre-train language models for improving the understanding of math problems.
Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing
In this paper, we propose an innovative Bit-mask Robust Contrastive knowledge Distillation (BRCD) method, specifically devised for the distillation of semantic hashing models.
JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving
Specially, we construct a Mixture-of-Experts~(MoE) architecture for modeling mathematical text, so as to capture the common mathematical knowledge across tasks.
Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning
Based on this finding, we propose a new approach that can deliberate the reasoning steps with tool interfaces, namely \textbf{DELI}.
JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding
Considering the complex nature of mathematical texts, we design a novel curriculum pre-training approach for improving the learning of mathematical PLMs, consisting of both basic and advanced courses.
