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pro vyhledávání: '"Sanyal, Debarshi Kumar"'
The title of a research paper communicates in a succinct style the main theme and, sometimes, the findings of the paper. Coming up with the right title is often an arduous task, and therefore, it would be beneficial to authors if title generation can
Externí odkaz:
http://arxiv.org/abs/2409.14602
Publikováno v:
Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing: IEM-ICDC 2021,pages 17--27
Financial sentiment analysis allows financial institutions like Banks and Insurance Companies to better manage the credit scoring of their customers in a better way. Financial domain uses specialized mechanisms which makes sentiment analysis difficul
Externí odkaz:
http://arxiv.org/abs/2405.01586
Autor:
Adhya, Suman, Sanyal, Debarshi Kumar
Topic modeling is a widely used approach for analyzing and exploring large document collections. Recent research efforts have incorporated pre-trained contextualized language models, such as BERT embeddings, into topic modeling. However, they often n
Externí odkaz:
http://arxiv.org/abs/2404.02115
Autor:
Banerjee, Soumya, Sanyal, Debarshi Kumar, Chattopadhyay, Samiran, Bhowmick, Plaban Kumar, Das, Partha Pratim
Digital libraries often face the challenge of processing a large volume of diverse document types. The manual collection and tagging of metadata can be a time-consuming and error-prone task. To address this, we aim to develop an automatic metadata ex
Externí odkaz:
http://arxiv.org/abs/2401.12220
Hallucination in text summarization refers to the phenomenon where the model generates information that is not supported by the input source document. Hallucination poses significant obstacles to the accuracy and reliability of the generated summarie
Externí odkaz:
http://arxiv.org/abs/2309.16781
Citations in scientific papers not only help us trace the intellectual lineage but also are a useful indicator of the scientific significance of the work. Citation intents prove beneficial as they specify the role of the citation in a given context.
Externí odkaz:
http://arxiv.org/abs/2304.12730
Autor:
Adhya, Suman, Sanyal, Debarshi Kumar
The TCPD-IPD dataset is a collection of questions and answers discussed in the Lower House of the Parliament of India during the Question Hour between 1999 and 2019. Although it is difficult to analyze such a huge collection manually, modern text ana
Externí odkaz:
http://arxiv.org/abs/2304.00235
Dropout is a widely used regularization trick to resolve the overfitting issue in large feedforward neural networks trained on a small dataset, which performs poorly on the held-out test subset. Although the effectiveness of this regularization trick
Externí odkaz:
http://arxiv.org/abs/2303.15973
Topic modeling has emerged as a dominant method for exploring large document collections. Recent approaches to topic modeling use large contextualized language models and variational autoencoders. In this paper, we propose a negative sampling mechani
Externí odkaz:
http://arxiv.org/abs/2303.14951
Autor:
Adhya, Suman, Sanyal, Debarshi Kumar
Topic modeling is a dominant method for exploring document collections on the web and in digital libraries. Recent approaches to topic modeling use pretrained contextualized language models and variational autoencoders. However, large neural topic mo
Externí odkaz:
http://arxiv.org/abs/2303.15350