15 citations · 37 across the 7 of their papers we have counts for
7 papers
SFR-RAG: Towards Contextually Faithful LLMs
Xuan-Phi Nguyen, Shrey Pandit, Senthil Purushwalkam +7
Retrieval Augmented Generation (RAG), a paradigm that integrates external contextual information with large language models (LLMs) to enhance factual accuracy and relevance, has em…
xGen-VideoSyn-1: High-fidelity Text-to-Video Synthesis with Compressed Representations
Can Qin, Congying Xia, Krithika Ramakrishnan +16
We present xGen-VideoSyn-1, a text-to-video (T2V) generation model capable of producing realistic scenes from textual descriptions. Building on recent advancements, such as OpenAI'…
BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion Models
Senthil Purushwalkam, Akash Gokul, Shafiq Joty +1
Recent text-to-image generation models have demonstrated incredible success in generating images that faithfully follow input prompts. However, the requirement of using words to de…
ConRad: Image Constrained Radiance Fields for 3D Generation from a Single Image
Senthil Purushwalkam, Nikhil Naik
We present a novel method for reconstructing 3D objects from a single RGB image. Our method leverages the latest image generation models to infer the hidden 3D structure while rema…
XGen-7B Technical Report
Erik Nijkamp, Tian Xie, Hiroaki Hayashi +22
Large Language Models (LLMs) have become ubiquitous across various domains, transforming the way we interact with information and conduct research. However, most high-performing LL…
Pose from Action: Unsupervised Learning of Pose Features based on Motion
Senthil Purushwalkam, Abhinav Gupta
Human actions are comprised of a sequence of poses. This makes videos of humans a rich and dense source of human poses. We propose an unsupervised method to learn pose features fro…