8 papers
LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Search
Nikhil Abhyankar, Sha Li, Sanchit Kabra +3
Recovering governing Ordinary Differential Equations (ODEs) from data is a central challenge in modeling dynamical systems across scientific domains. Existing approaches cast disco…
LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs
Sanchit Kabra, Nikhil Abhyankar, Saaketh Desai +2
Scientific discovery is a closed-loop process in which hypotheses guide data acquisition and observations refine the hypothesis space. Yet most approaches reduce discovery to super…
LLEMA: Evolutionary Search with LLMs for Multi-Objective Materials Discovery
Nikhil Abhyankar, Sanchit Kabra, Saaketh Desai +1
Materials discovery requires navigating vast chemical and structural spaces while satisfying multiple, often conflicting, objectives. We present LLM-guided Evolution for MAterials…
SURFACEBENCH: A Geometry-Aware Benchmark for Symbolic Surface Discovery
Sanchit Kabra, Shobhnik Kriplani, Parshin Shojaee +1
Equation discovery from data is a central challenge in machine learning for science, which requires the recovery of concise symbolic expressions that govern complex physical and ge…
Beyond Single Bugs: Benchmarking Large Language Models for Multi-Vulnerability Detection
Chinmay Pushkar, Sanchit Kabra, Dhruv Kumar +1
Large Language Models (LLMs) have demonstrated significant potential in automated software security, particularly in vulnerability detection. However, existing benchmarks primarily…
RUST-BENCH: Benchmarking LLM Reasoning on Unstructured Text within Structured Tables
Nikhil Abhyankar, Purvi Chaurasia, Sanchit Kabra +3
Existing tabular reasoning benchmarks mostly test models on small, uniform tables, underrepresenting the complexity of real-world data and giving an incomplete view of Large Langua…