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Found 4 papers, 3 papers with code
Imitate Before Detect: Aligning Machine Stylistic Preference for Machine-Revised Text Detection
Large Language Models (LLMs) have revolutionized text generation, making detecting machine-generated text increasingly challenging.
ContextGNN: Beyond Two-Tower Recommendation Systems
Recommendation systems predominantly utilize two-tower architectures, which evaluate user-item rankings through the inner product of their respective embeddings.
RelBench: A Benchmark for Deep Learning on Relational Databases
We use RelBench to conduct the first comprehensive study of Relational Deep Learning (RDL) (Fey et al., 2024), which combines graph neural network predictive models with (deep) tabular models that extract initial entity-level representations from raw tables.
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning
We present PyTorch Frame, a PyTorch-based framework for deep learning over multi-modal tabular data.
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