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Found 4 papers, 2 papers with code
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
Large language models (LLM), such as Google's Minerva and OpenAI's GPT families, are becoming increasingly capable of solving mathematical quantitative reasoning problems.
Autoformalization with Large Language Models
Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs.
Ranked #1 on
Automated Theorem Proving
on miniF2F-test
(using extra training data)
When adversarial examples are excusable
Qualitatively, the remaining adversarial errors are similar to test errors on difficult examples.
Self-attention Does Not Need $O(n^2)$ Memory
We present a very simple algorithm for attention that requires $O(1)$ memory with respect to sequence length and an extension to self-attention that requires $O(\log n)$ memory.
