4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.AI2025★ 1 cited
Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning
Haiming Wang, Mert Unsal, Xiaohan Lin +37
We introduce Kimina-Prover Preview, a large language model that pioneers a novel reasoning-driven exploration paradigm for formal theorem proving, as showcased in this preview rele…
cs.SE2025★ 2 cited
Challenges and Paths Towards AI for Software Engineering
Alex Gu, Naman Jain, Wen-Ding Li +7
AI for software engineering has made remarkable progress recently, becoming a notable success within generative AI. Despite this, there are still many challenges that need to be ad…
cs.LG2024★ 4 cited
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models
Alex Havrilla, Andrew Dai, Laura O'Mahony +17
Synthetic data generation with Large Language Models is a promising paradigm for augmenting natural data over a nearly infinite range of tasks. Given this variety, direct compariso…