5 citations · 8 across the 5 of their papers we have counts for
5 papers
Topic Segmentation of Semi-Structured and Unstructured Conversational Datasets using Language Models
Reshmi Ghosh, Harjeet Singh Kajal, Sharanya Kamath +4
Breaking down a document or a conversation into multiple contiguous segments based on its semantic structure is an important and challenging problem in NLP, which can assist many d…
On Surgical Fine-tuning for Language Encoders
Abhilasha Lodha, Gayatri Belapurkar, Saloni Chalkapurkar +5
Fine-tuning all the layers of a pre-trained neural language encoder (either using all the parameters or using parameter-efficient methods) is often the de-facto way of adapting it…
Localizing and Editing Knowledge in Text-to-Image Generative Models
Samyadeep Basu, Nanxuan Zhao, Vlad Morariu +2
Text-to-Image Diffusion Models such as Stable-Diffusion and Imagen have achieved unprecedented quality of photorealism with state-of-the-art FID scores on MS-COCO and other generat…
EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods
Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj +5
A plethora of text-guided image editing methods have recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models such as Imag…
Strong Baselines for Parameter Efficient Few-Shot Fine-tuning
Samyadeep Basu, Daniela Massiceti, Shell Xu Hu +1
Few-shot classification (FSC) entails learning novel classes given only a few examples per class after a pre-training (or meta-training) phase on a set of base classes. Recent work…