Zobrazeno 1 - 10
of 2 143
pro vyhledávání: '"A., Varshini"'
Autor:
Lovering, Charles, Krumdick, Michael, Lai, Viet Dac, Kumar, Nilesh, Reddy, Varshini, Koncel-Kedziorski, Rik, Tanner, Chris
Some information is factual (e.g., "Paris is in France"), whereas other information is probabilistic (e.g., "the coin flip will be a [Heads/Tails]."). We believe that good Language Models (LMs) should understand and reflect this nuance. Our work inve
Externí odkaz:
http://arxiv.org/abs/2410.16007
Autor:
R, Sanjjushri Varshini, Mahadevan, Rohith, S, Bagiya Lakshmi, Periasamy, Mathivanan, Raman, Raja CSP, M, Lokesh
This research tackles the challenge of speckle noise in Synthetic Aperture Radar (SAR) space data, a prevalent issue that hampers the clarity and utility of SAR images. The study presents a comparative analysis of six distinct speckle noise reduction
Externí odkaz:
http://arxiv.org/abs/2408.08774
Training large language models (LLMs) for pretraining or adapting to new tasks and domains has become increasingly critical as their applications expand. However, as the model and the data sizes grow, the training process presents significant memory
Externí odkaz:
http://arxiv.org/abs/2406.17296
FActScore has gained popularity as a metric to estimate the factuality of long-form texts generated by Large Language Models (LLMs) in English. However, there has not been any work in studying the behavior of FActScore in other languages. This paper
Externí odkaz:
http://arxiv.org/abs/2406.19415
Autor:
Lai, Viet Dac, Krumdick, Michael, Lovering, Charles, Reddy, Varshini, Schmidt, Craig, Tanner, Chris
The financial domain frequently deals with large numbers of long documents that are essential for daily operations. Significant effort is put towards automating financial data analysis. However, a persistent challenge, not limited to the finance doma
Externí odkaz:
http://arxiv.org/abs/2406.14394
The detection of cardiovascular diseases (CVD) using machine learning techniques represents a significant advancement in medical diagnostics, aiming to enhance early detection, accuracy, and efficiency. This study explores a comparative analysis of v
Externí odkaz:
http://arxiv.org/abs/2405.17059
Autor:
Sri, S Deepika, S, Mohammed Aadil, R, Sanjjushri Varshini, Raman, Raja CSP, Rajagopal, Gopinath, Chan, S Taranath
In the contemporary landscape of technological advancements, the automation of manual processes is crucial, compelling the demand for huge datasets to effectively train and test machines. This research paper is dedicated to the exploration and implem
Externí odkaz:
http://arxiv.org/abs/2404.10678
Autor:
Zhong, Xinzhi, Zhou, Yang, Kamaraj, Varshini, Zhou, Zhenhao, Kontar, Wissam, Negrut, Dan, Lee, John D., Ahn, Soyoung
This paper develops a novel car-following control method to reduce voluntary driver interventions and improve traffic stability in Automated Vehicles (AVs). Through a combination of experimental and empirical analysis, we show how voluntary driver in
Externí odkaz:
http://arxiv.org/abs/2404.05832
Autor:
Schmidt, Craig W., Reddy, Varshini, Zhang, Haoran, Alameddine, Alec, Uzan, Omri, Pinter, Yuval, Tanner, Chris
Tokenization is a foundational step in natural language processing (NLP) tasks, bridging raw text and language models. Existing tokenization approaches like Byte-Pair Encoding (BPE) originate from the field of data compression, and it has been sugges
Externí odkaz:
http://arxiv.org/abs/2402.18376
Autor:
Reddy, Varshini, Koncel-Kedziorski, Rik, Lai, Viet Dac, Krumdick, Michael, Lovering, Charles, Tanner, Chris
For large language models (LLMs) to be effective in the financial domain -- where each decision can have a significant impact -- it is necessary to investigate realistic tasks and data. Financial professionals often interact with documents that are h
Externí odkaz:
http://arxiv.org/abs/2401.06915