3 papers
cs.LG2025
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
Lakshmi Nair, Ian Trase, Mark Kim
We present a novel reasoning approach called Flow-of-Options (FoO), designed to address intrinsic biases in Large Language Models (LLMs). Flow-of-Options enables LLMs to systematic…
cs.CV2024
Improved Generation of Synthetic Imaging Data Using Feature-Aligned Diffusion
Lakshmi Nair
Synthetic data generation is an important application of machine learning in the field of medical imaging. While existing approaches have successfully applied fine-tuned diffusion…
cs.LG2024
CLIP-Embed-KD: Computationally Efficient Knowledge Distillation Using Embeddings as Teachers
Lakshmi Nair
Contrastive Language-Image Pre-training (CLIP) has been shown to improve zero-shot generalization capabilities of language and vision models. In this paper, we extend CLIP for effi…