Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Karisani P"'
Autor:
Liu, Jiateng, Ai, Lin, Liu, Zizhou, Karisani, Payam, Hui, Zheng, Fung, May, Nakov, Preslav, Hirschberg, Julia, Ji, Heng
Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the ability to capture the broader motives and the impacts of such content
Externí odkaz:
http://arxiv.org/abs/2409.18997
Autor:
Daneshvaramoli, Mohammadreza, Karisani, Helia, Lechowicz, Adam, Sun, Bo, Musco, Cameron, Hajiesmaili, Mohammad
In the online knapsack problem, the goal is to pack items arriving online with different values and weights into a capacity-limited knapsack to maximize the total value of the accepted items. We study \textit{learning-augmented} algorithms for this p
Externí odkaz:
http://arxiv.org/abs/2406.18752
Autor:
Karisani, Payam, Ji, Heng
Evaluating the veracity of everyday claims is time consuming and in some cases requires domain expertise. We empirically demonstrate that the commonly used fact checking pipeline, known as the retriever-reader, suffers from performance deterioration
Externí odkaz:
http://arxiv.org/abs/2403.18671
Autor:
Monsefi, Amin Karimi, Karisani, Payam, Zhou, Mengxi, Choi, Stacey, Doble, Nathan, Ji, Heng, Parthasarathy, Srinivasan, Ramnath, Rajiv
Standard modern machine-learning-based imaging methods have faced challenges in medical applications due to the high cost of dataset construction and, thereby, the limited labeled training data available. Additionally, upon deployment, these methods
Externí odkaz:
http://arxiv.org/abs/2402.06190
Named entity recognition is a key component of Information Extraction (IE), particularly in scientific domains such as biomedicine and chemistry, where large language models (LLMs), e.g., ChatGPT, fall short. We investigate the applicability of trans
Externí odkaz:
http://arxiv.org/abs/2401.10472
Autor:
Karisani, Payam
We propose a semi-supervised text classifier based on self-training using one positive and one negative property of neural networks. One of the weaknesses of self-training is the semantic drift problem, where noisy pseudo-labels accumulate over itera
Externí odkaz:
http://arxiv.org/abs/2401.00575
Open-domain conversational search (ODCS) aims to provide valuable, up-to-date information, while maintaining natural conversations to help users refine and ultimately answer information needs. However, creating an effective and robust ODCS agent is c
Externí odkaz:
http://arxiv.org/abs/2304.02233
Autor:
Lin, Chen, Yousefi, Safoora, Kahoro, Elvis, Karisani, Payam, Liang, Donghai, Sarnat, Jeremy, Agichtein, Eugene
Publikováno v:
JMIR Form Res. 2022 Oct 25
Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecasting and monitoring research using artificial neural networks (ANNs).
Externí odkaz:
http://arxiv.org/abs/2211.05267
We consider the problem of generating hypothesis from data based on ideas from logic. We introduce a notion of barcodes, which we call sequent barcodes, that mirrors the barcodes in persistent homology theory in topological data analysis. We prove a
Externí odkaz:
http://arxiv.org/abs/2208.01450
Mining user-generated data often suffers from the lack of enough labeled data, short document lengths, and the informal user language. In this paper, we propose a novel active learning model to overcome these obstacles in the tasks tailored for query
Externí odkaz:
http://arxiv.org/abs/2112.02611