3 papers
cs.CL2026
FLARE: Few-shot Learning-based Adaptive Reflective Engine
Dhanasekar Sundararaman, Bharat Gandhi, Aashna Garg +1
Large language models (LLMs) are increasingly deployed in complex, compound AI systems where performance hinges on the quality of prompts. Recent state-of-the-art optimizers like G…
cs.CL2025
LOCUS: A System and Method for Low-Cost Customization for Universal Specialization
Dhanasekar Sundararaman, Keying Li, Wayne Xiong +1
We present LOCUS (LOw-cost Customization for Universal Specialization), a pipeline that consumes few-shot data to streamline the construction and training of NLP models through tar…
cs.CV2025
Evaluating Hallucination in Large Vision-Language Models based on Context-Aware Object Similarities
Shounak Datta, Dhanasekar Sundararaman
Despite their impressive performance on multi-modal tasks, large vision-language models (LVLMs) tend to suffer from hallucinations. An important type is object hallucination, where…