6 citations · 17 across the 32 of their papers we have counts for
10 papers · 1 filter
Survey of User Interface Design and Interaction Techniques in Generative AI Applications
Reuben Luera, Ryan A. Rossi, Alexa Siu +10
The applications of generative AI have become extremely impressive, and the interplay between users and AI is even more so. Current human-AI interaction literature has taken a broa…
A Survey of Small Language Models
Chien Van Nguyen, Xuan Shen, Ryan Aponte +25
Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, maki…
Quantifying reliance on external information over parametric knowledge during Retrieval Augmented Generation (RAG) using mechanistic analysis
Reshmi Ghosh, Rahul Seetharaman, Hitesh Wadhwa +6
Retrieval Augmented Generation (RAG) is a widely used approach for leveraging external context in several natural language applications such as question answering and information r…
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning
Soumya Suvra Ghosal, Samyadeep Basu, Soheil Feizi +1
Image-text contrastive models such as CLIP learn transferable and robust representations for zero-shot transfer to a variety of downstream tasks. However, to obtain strong downstre…
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries
Hitesh Wadhwa, Rahul Seetharaman, Somyaa Aggarwal +6
Retrieval Augmented Generation (RAG) enriches the ability of language models to reason using external context to augment responses for a given user prompt. This approach has risen…
Understanding Information Storage and Transfer in Multi-modal Large Language Models
Samyadeep Basu, Martin Grayson, Cecily Morrison +3
Understanding the mechanisms of information storage and transfer in Transformer-based models is important for driving model understanding progress. Recent work has studied these me…
Improving Compositional Attribute Binding in Text-to-Image Generative Models via Enhanced Text Embeddings
Arman Zarei, Keivan Rezaei, Samyadeep Basu +4
Text-to-image diffusion-based generative models have the stunning ability to generate photo-realistic images and achieve state-of-the-art low FID scores on challenging image genera…
Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP
Sriram Balasubramanian, Samyadeep Basu, Soheil Feizi
Recent work has explored how individual components of the CLIP-ViT model contribute to the final representation by leveraging the shared image-text representation space of CLIP. Th…
On Mechanistic Knowledge Localization in Text-to-Image Generative Models
Samyadeep Basu, Keivan Rezaei, Priyatham Kattakinda +5
Identifying layers within text-to-image models which control visual attributes can facilitate efficient model editing through closed-form updates. Recent work, leveraging causal tr…
Rethinking Artistic Copyright Infringements in the Era of Text-to-Image Generative Models
Mazda Moayeri, Samyadeep Basu, Sriram Balasubramanian +4
Recent text-to-image generative models such as Stable Diffusion are extremely adept at mimicking and generating copyrighted content, raising concerns amongst artists that their uni…