Deep reasoning

I study how causality and other formal reasoning systems can improve AI reasoning and help solve complex problems that require exploration over thousands of steps. See Plan*RAG for an example on how solving complex tasks can be abstracted out as planning over a directed acyclic graph.

Improving AI reasoning

• A planning algorithm that utilize LLMs for completing complex tasks (Verma et al., 2024)
• Axiomatic training framework for teaching compositional reasoning to AI models (Vashishtha et al., 2025)
• LiveDRBench: A benchmark for Deep Research (Java et al., 2025)

Text-based optimization for generative AI

• Optimizing prompts for large language models (Juneja et al., 2025; Srivastava et al., 2024)