Showing cs.CLShow all
3 papers · 1 filter
cs.CL2026
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…
cs.CL2024
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…
cs.CL2024
SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation
Abhishek Divekar, Greg Durrett
It is often desirable to distill the capabilities of large language models (LLMs) into smaller student models due to compute and memory constraints. One way to do this for classifi…