25 citations · 26 across the 5 of their papers we have counts for
6 papers
Decaf: Improving Neural Decompilation with Automatic Feedback and Search
Alexander Shypula, Osbert Bastani, Edward Schwartz
Decompilers are useful tools used in reverse engineering to understand compiled source code. Reconstructing source code from compiled binaries is a challenging task, because high-l…
Evaluating the Diversity and Quality of LLM Generated Content
Alexander Shypula, Shuo Li, Botong Zhang +3
Recent work suggests that preference-tuning techniques -- such as Reinforcement Learning from Human Feedback (RLHF) methods like PPO and GRPO, as well as alternatives like DPO -- r…
LLM Program Optimization via Retrieval Augmented Search
Sagnik Anupam, Alexander Shypula, Osbert Bastani
Recent work has demonstrated the potential of large language models (LLMs) for program optimization, a key challenge in programming languages. We propose a blackbox adaptation meth…
Explain-then-Translate: An Analysis on Improving Program Translation with Self-generated Explanations
Zilu Tang, Mayank Agarwal, Alex Shypula +4
This work explores the use of self-generated natural language explanations as an intermediate step for code-to-code translation with language models. Across three types of explanat…
Learning Performance-Improving Code Edits
Alexander Shypula, Aman Madaan, Yimeng Zeng +7
With the decline of Moore's law, optimizing program performance has become a major focus of software research. However, high-level optimizations such as API and algorithm changes r…
Learning to Superoptimize Real-world Programs
Alex Shypula, Pengcheng Yin, Jeremy Lacomis +3
Program optimization is the process of modifying software to execute more efficiently. Superoptimizers attempt to find the optimal program by employing significantly more expensive…