Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Harsha, Sai Sree"'
Autor:
Dixit, Tanay, Lee, Daniel, Fang, Sally, Harsha, Sai Sree, Sureshan, Anirudh, Maharaj, Akash, Li, Yunyao
Large Language Models (LLMs) are increasingly integrated into diverse applications. The rapid evolution of LLMs presents opportunities for developers to enhance applications continuously. However, this constant adaptation can also lead to performance
Externí odkaz:
http://arxiv.org/abs/2409.03928
Autor:
Zhu, Zhengyuan, Lee, Daniel, Zhang, Hong, Harsha, Sai Sree, Feujio, Loic, Maharaj, Akash, Li, Yunyao
Recent advancements in retrieval-augmented generation (RAG) have demonstrated impressive performance in the question-answering (QA) task. However, most previous works predominantly focus on text-based answers. While some studies address multimodal da
Externí odkaz:
http://arxiv.org/abs/2408.08521
Video editing methods based on diffusion models that rely solely on a text prompt for the edit are hindered by the limited expressive power of text prompts. Thus, incorporating a reference target image as a visual guide becomes desirable for precise
Externí odkaz:
http://arxiv.org/abs/2404.12541
Autor:
Karmali, Tejan, Atrishi, Abhinav, Harsha, Sai Sree, Agrawal, Susmit, Jampani, Varun, Babu, R. Venkatesh
In this work, we introduce LEAD, an approach to discover landmarks from an unannotated collection of category-specific images. Existing works in self-supervised landmark detection are based on learning dense (pixel-level) feature representations from
Externí odkaz:
http://arxiv.org/abs/2204.02958