Math
525 papers with code • 0 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Math
Libraries
Use these libraries to find Math models and implementations
MathBench
GSM-Plus
DART-Math-Hard
DART-Math-Uniform
Most implemented papers
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
We explore how generating a chain of thought -- a series of intermediate reasoning steps -- significantly improves the ability of large language models to perform complex reasoning.
GPT-4 Technical Report
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs.
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
We propose Activation-aware Weight Quantization (AWQ), a hardware-friendly approach for LLM low-bit weight-only quantization.
Translating Math Formula Images to LaTeX Sequences Using Deep Neural Networks with Sequence-level Training
tatp22/multidim-positional-encoding
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The encoder is a convolutional neural network (CNN) that transforms images into a group of feature maps.
PaLM: Scaling Language Modeling with Pathways
lucidrains/CoCa-pytorch
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Google Research 2022
To further our understanding of the impact of scale on few-shot learning, we trained a 540-billion parameter, densely activated, Transformer language model, which we call Pathways Language Model PaLM.
Mistral 7B
We introduce Mistral 7B v0. 1, a 7-billion-parameter language model engineered for superior performance and efficiency.
ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
thudm/chatglm-6b
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We introduce ChatGLM, an evolving family of large language models that we have been developing over time.
The Matrix Calculus You Need For Deep Learning
This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks.
Full Page Handwriting Recognition via Image to Sequence Extraction
kingyiusuen/image-to-latex
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We present a Neural Network based Handwritten Text Recognition (HTR) model architecture that can be trained to recognize full pages of handwritten or printed text without image segmentation.
Training Verifiers to Solve Math Word Problems
State-of-the-art language models can match human performance on many tasks, but they still struggle to robustly perform multi-step mathematical reasoning.
