Zobrazeno 1 - 10
of 34 773
pro vyhledávání: '"Rangan A"'
Electron cryomicroscopy (cryo-EM) is a technique in structural biology used to reconstruct accurate volumetric maps of molecules. One step of the cryo-EM pipeline involves solving an inverse-problem. This inverse-problem, referred to as \textit{ab-in
Externí odkaz:
http://arxiv.org/abs/2411.13263
Autor:
Bomfin, Roberto, Bazzi, Ahmad, Guo, Hao, Lee, Hyeongtaek, Mezzavilla, Marco, Rangan, Sundeep, Choi, Junil, Chafii, Marwa
The following paper provides a multi-band channel measurement analysis on the frequency range (FR)3. This study focuses on the FR3 low frequencies 6.5 GHz and 8.75 GHz with a setup tailored to the context of integrated sensing and communication (ISAC
Externí odkaz:
http://arxiv.org/abs/2411.12888
Autor:
Savage, Thomas, Ma, Stephen, Boukil, Abdessalem, Patel, Vishwesh, Rangan, Ekanath, Rodriguez, Ivan, Chen, Jonathan H
Large Language Model (LLM) fine tuning is underutilized in the field of medicine. Two of the most common methods of fine tuning are Supervised Fine Tuning (SFT) and Direct Preference Optimization (DPO), but there is little guidance informing users wh
Externí odkaz:
http://arxiv.org/abs/2409.12741
Autor:
Chen, Qi, Geng, Xiubo, Rosset, Corby, Buractaon, Carolyn, Lu, Jingwen, Shen, Tao, Zhou, Kun, Xiong, Chenyan, Gong, Yeyun, Bennett, Paul, Craswell, Nick, Xie, Xing, Yang, Fan, Tower, Bryan, Rao, Nikhil, Dong, Anlei, Jiang, Wenqi, Liu, Zheng, Li, Mingqin, Liu, Chuanjie, Li, Zengzhong, Majumder, Rangan, Neville, Jennifer, Oakley, Andy, Risvik, Knut Magne, Simhadri, Harsha Vardhan, Varma, Manik, Wang, Yujing, Yang, Linjun, Yang, Mao, Zhang, Ce
Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals. In this paper, we introduce MS MARCO Web Search, the first large-scale information-rich web dataset, featuring millions of real clicked
Externí odkaz:
http://arxiv.org/abs/2405.07526
Autor:
McGrouther, Caroline C., Rangan, Aaditya V., Di Florio, Arianna, Elman, Jeremy A., Schork, Nicholas J., Kelsoe, John
Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. In this paper, we leverage recent advances in heterogeneity analy
Externí odkaz:
http://arxiv.org/abs/2405.00159
The upper mid-band (FR3) has been recently attracting interest for new generation of mobile networks, as it provides a promising balance between spectrum availability and coverage, which are inherent limitations of the sub 6GHz and millimeter wave ba
Externí odkaz:
http://arxiv.org/abs/2404.17069
Autor:
Suri, Siddharth, Counts, Scott, Wang, Leijie, Chen, Chacha, Wan, Mengting, Safavi, Tara, Neville, Jennifer, Shah, Chirag, White, Ryen W., Andersen, Reid, Buscher, Georg, Manivannan, Sathish, Rangan, Nagu, Yang, Longqi
Until recently, search engines were the predominant method for people to access online information. The recent emergence of large language models (LLMs) has given machines new capabilities such as the ability to generate new digital artifacts like te
Externí odkaz:
http://arxiv.org/abs/2404.04268
Autor:
Wan, Mengting, Safavi, Tara, Jauhar, Sujay Kumar, Kim, Yujin, Counts, Scott, Neville, Jennifer, Suri, Siddharth, Shah, Chirag, White, Ryen W, Yang, Longqi, Andersen, Reid, Buscher, Georg, Joshi, Dhruv, Rangan, Nagu
Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and application. However, most existing methods for producing label taxonomies and
Externí odkaz:
http://arxiv.org/abs/2403.12173
Autor:
Rangan, Keshav, Yin, Yiqiao
This study presents an innovative enhancement to retrieval-augmented generation (RAG) systems by seamlessly integrating fine-tuned large language models (LLMs) with vector databases. This integration capitalizes on the combined strengths of structure
Externí odkaz:
http://arxiv.org/abs/2402.17081
This technical report presents the training methodology and evaluation results of the open-source multilingual E5 text embedding models, released in mid-2023. Three embedding models of different sizes (small / base / large) are provided, offering a b
Externí odkaz:
http://arxiv.org/abs/2402.05672