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Found 3 papers, 2 papers with code
A Survey on Deep Learning for Theorem Proving
Theorem proving is a fundamental aspect of mathematics, spanning from informal reasoning in mathematical language to rigorous derivations in formal systems.
The Synergy of Speculative Decoding and Batching in Serving Large Language Models
Large Language Models (LLMs) like GPT are state-of-the-art text generation models that provide significant assistance in daily routines.
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
To minimize the overheads associated with distributed computations, DistDGL uses a high-quality and light-weight min-cut graph partitioning algorithm along with multiple balancing constraints.
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