5 papers
VESTA: Visual Exploration with Statistical Tool Agents
William Rudman, Abhishek Divekar, Kanishk Jain +6
Fitting quantitative models to data is a central step in scientific workflows, yet it remains one of the least automated. Recent agent-based systems leverage language and vision-la…
Statistically Reliable LLM-Based Ranking Evaluation via Prediction-Powered Inference
Abhishek Divekar
With PRECISE, we extended Prediction-Powered Inference to produce bias-corrected estimates of ranking evaluation metrics by combining a small human-labeled set with a large LLM-jud…
When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges
Parth Darshan, Abhishek Divekar
Customizing an LLM judge to a specific problem or domain often involves optimizing its prompt across multiple evaluation criteria simultaneously. Textual gradient methods automate…
CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs
Suhas S Kowshik, Abhishek Divekar, Vijit Malik
Large language models (LLMs) have demonstrated remarkable performance in diverse tasks using zero-shot and few-shot prompting. Even though their capabilities of data synthesis have…
Benchmarking datasets for Anomaly-based Network Intrusion Detection: KDD CUP 99 alternatives
Abhishek Divekar, Meet Parekh, Vaibhav Savla +2
Machine Learning has been steadily gaining traction for its use in Anomaly-based Network Intrusion Detection Systems (A-NIDS). Research into this domain is frequently performed usi…