Zobrazeno 1 - 10
of 38 392
pro vyhledávání: '"Anoop, A."'
Physical reasoning is an important skill needed for robotic agents when operating in the real world. However, solving such reasoning problems often involves hypothesizing and reflecting over complex multi-body interactions under the effect of a multi
Externí odkaz:
http://arxiv.org/abs/2411.08027
Autor:
Gao, Yanjun, Myers, Skatje, Chen, Shan, Dligach, Dmitriy, Miller, Timothy A, Bitterman, Danielle, Chen, Guanhua, Mayampurath, Anoop, Churpek, Matthew, Afshar, Majid
Large language models (LLMs) are being explored for diagnostic decision support, yet their ability to estimate pre-test probabilities, vital for clinical decision-making, remains limited. This study evaluates two LLMs, Mistral-7B and Llama3-70B, usin
Externí odkaz:
http://arxiv.org/abs/2411.04962
Autor:
Jain, Sparsh, Sankar, Ashwin, Choudhary, Devilal, Suman, Dhairya, Narasimhan, Nikhil, Khan, Mohammed Safi Ur Rahman, Kunchukuttan, Anoop, Khapra, Mitesh M, Dabre, Raj
Automatic Speech Translation (AST) datasets for Indian languages remain critically scarce, with public resources covering fewer than 10 of the 22 official languages. This scarcity has resulted in AST systems for Indian languages lagging far behind th
Externí odkaz:
http://arxiv.org/abs/2411.04699
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
Autor:
Ghosal, Shubham, Singh, Manmeet, Ghude, Sachin, Kamath, Harsh, SB, Vaisakh, Wasekar, Subodh, Mahajan, Anoop, Dashtian, Hassan, Yang, Zong-Liang, Young, Michael, Niyogi, Dev
This study presents an innovative approach to creating a dynamic, AI based emission inventory system for use with the Weather Research and Forecasting model coupled with Chemistry (WRF Chem), designed to simulate vehicular and other anthropogenic emi
Externí odkaz:
http://arxiv.org/abs/2410.19773
Along with the partition of a planar bounded domain $\Omega$ by the nodal set of a fixed eigenfunction of the Laplace operator in $\Omega$, one can consider another natural partition of $\Omega$ by, roughly speaking, gradient flow lines of a special
Externí odkaz:
http://arxiv.org/abs/2410.07811
Autor:
Lawton, Neal, Padmakumar, Aishwarya, Gaspers, Judith, FitzGerald, Jack, Kumar, Anoop, Steeg, Greg Ver, Galstyan, Aram
QLoRA reduces the memory-cost of fine-tuning a large language model (LLM) with LoRA by quantizing the base LLM. However, quantization introduces quantization errors that negatively impact model performance after fine-tuning. In this paper we introduc
Externí odkaz:
http://arxiv.org/abs/2410.14713
The aim of this manuscript is to address non-linear differential equations of the Lane Emden equation of second order using the shifted Legendre neural network (SLNN) method. Here all the equations are classified as singular initial value problems. T
Externí odkaz:
http://arxiv.org/abs/2410.05409
Autor:
Melcer, Daniel, Gonugondla, Sujan, Perera, Pramuditha, Qian, Haifeng, Chiang, Wen-Hao, Wang, Yanjun, Jain, Nihal, Garg, Pranav, Ma, Xiaofei, Deoras, Anoop
It is common to reject undesired outputs of Large Language Models (LLMs); however, current methods to do so require an excessive amount of computation, or severely distort the distribution of outputs. We present a method to balance the distortion of
Externí odkaz:
http://arxiv.org/abs/2410.01103
Autor:
Myers, Skatje, Miller, Timothy A., Gao, Yanjun, Churpek, Matthew M., Mayampurath, Anoop, Dligach, Dmitriy, Afshar, Majid
Objective: Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation (RAG) offers a solution by facilitating reasoning over large text sou
Externí odkaz:
http://arxiv.org/abs/2409.15163