3 papers
cs.LG2026
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…
cs.SE2026
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…
cs.CL2026
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…