Zobrazeno 1 - 10
of 6 577
pro vyhledávání: '"A. Sumanth"'
Autor:
Doddapaneni, Sumanth, Khan, Mohammed Safi Ur Rahman, Venkatesh, Dilip, Dabre, Raj, Kunchukuttan, Anoop, Khapra, Mitesh M.
Evaluating machine-generated text remains a significant challenge in NLP, especially for non-English languages. Current methodologies, including automated metrics, human assessments, and LLM-based evaluations, predominantly focus on English, revealin
Externí odkaz:
http://arxiv.org/abs/2410.13394
This paper reviews the large spectrum of methods for generating robot motion proposed over the 50 years of robotics research culminating in recent developments. It crosses the boundaries of methodologies, typically not surveyed together, from those t
Externí odkaz:
http://arxiv.org/abs/2410.12172
Geolocation plays a critical role in understanding the Internet. In this work, we provide an in-depth analysis of operator-misreported geolocation. Using a bandwidth-efficient methodology, we find in May 2024 that only a small percentage (1.5%) of va
Externí odkaz:
http://arxiv.org/abs/2409.19109
Autor:
Sivaramakrishnan, Aravind, Tangirala, Sumanth, Ramesh, Dhruv Metha, Granados, Edgar, Bekris, Kostas E.
This paper aims to increase the safety and reliability of executing trajectories planned for robots with non-trivial dynamics given a light-weight, approximate dynamics model. Scenarios include mobile robots navigating through workspaces with imperfe
Externí odkaz:
http://arxiv.org/abs/2409.11522
Autor:
McManus, Maxwell, Rinchen, Tenzin, Dey, Annoy, Thota, Sumanth, Zhang, Zhaoxi, Hu, Jiangqi, Wang, Xi, Ji, Mingyue, Mastronarde, Nicholas, Bentley, Elizabeth Serena, Medley, Michael, Guan, Zhangyu
In this work, we present a new federation framework for UnionLabs, an innovative cloud-based resource-sharing infrastructure designed for next-generation (NextG) and Internet of Things (IoT) over-the-air (OTA) experiments. The framework aims to reduc
Externí odkaz:
http://arxiv.org/abs/2408.14460
Autor:
Prabhu, Sumanth
Self-ensembling techniques with diverse reasoning paths such as Self-Consistency have demonstrated remarkable performance gains in text generation with Large Language Models (LLMs). However, such techniques depend on the availability of an accurate a
Externí odkaz:
http://arxiv.org/abs/2408.08869
Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting using robust methods. We demonstrate a proof of concept of using a data-driven supervised classification fra
Externí odkaz:
http://arxiv.org/abs/2408.05590
Autor:
Hebert, Liam, Sayana, Krishna, Jash, Ambarish, Karatzoglou, Alexandros, Sodhi, Sukhdeep, Doddapaneni, Sumanth, Cai, Yanli, Kuzmin, Dima
Understanding the nuances of a user's extensive interaction history is key to building accurate and personalized natural language systems that can adapt to evolving user preferences. To address this, we introduce PERSOMA, Personalized Soft Prompt Ada
Externí odkaz:
http://arxiv.org/abs/2408.00960
Autor:
Magistri, Federico, Läbe, Thomas, Marks, Elias, Nagulavancha, Sumanth, Pan, Yue, Smitt, Claus, Klingbeil, Lasse, Halstead, Michael, Kuhlmann, Heiner, McCool, Chris, Behley, Jens, Stachniss, Cyrill
As the world population is expected to reach 10 billion by 2050, our agricultural production system needs to double its productivity despite a decline of human workforce in the agricultural sector. Autonomous robotic systems are one promising pathway
Externí odkaz:
http://arxiv.org/abs/2407.13304
Large Language Models (LLMs) are increasingly relied upon to evaluate text outputs of other LLMs, thereby influencing leaderboards and development decisions. However, concerns persist over the accuracy of these assessments and the potential for misle
Externí odkaz:
http://arxiv.org/abs/2406.13439