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Found 5 papers, 1 papers with code
Arithmetic Reasoning with LLM: Prolog Generation & Permutation
We hypothesize that an LLM should focus on extracting predicates and generating symbolic formulas from the math problem description so that the underlying calculation can be done via an external code interpreter.
Exploring an LM to generate Prolog Predicates from Mathematics Questions
Consequently, we employ chain-of-thought to fine-tune LLaMA7B as a baseline model and develop other fine-tuned LLaMA7B models for the generation of Prolog code, Prolog code + chain-of-thought, and chain-of-thought + Prolog code, respectively.
Simple and Efficient Heterogeneous Graph Neural Network
Heterogeneous graph neural networks (HGNNs) have powerful capability to embed rich structural and semantic information of a heterogeneous graph into node representations.
Characterizing and Understanding Distributed GNN Training on GPUs
Graph neural network (GNN) has been demonstrated to be a powerful model in many domains for its effectiveness in learning over graphs.
FA-GAN: Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution
High-resolution magnetic resonance images can provide fine-grained anatomical information, but acquiring such data requires a long scanning time.
