Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Gosangi, Rakesh"'
In this paper, we study the importance of context in predicting the citation worthiness of sentences in scholarly articles. We formulate this problem as a sequence labeling task solved using a hierarchical BiLSTM model. We contribute a new benchmark
Externí odkaz:
http://arxiv.org/abs/2104.08962
Autor:
Mehnaz, Laiba, Mahata, Debanjan, Gosangi, Rakesh, Gunturi, Uma Sushmitha, Jain, Riya, Gupta, Gauri, Kumar, Amardeep, Lee, Isabelle, Acharya, Anish, Shah, Rajiv Ratn
Code-switching is the communication phenomenon where speakers switch between different languages during a conversation. With the widespread adoption of conversational agents and chat platforms, code-switching has become an integral part of written co
Externí odkaz:
http://arxiv.org/abs/2104.08578
Autor:
Anand, Sarthak, Gupta, Pradyumna, Yadav, Hemant, Mahata, Debanjan, Gosangi, Rakesh, Zhang, Haimin, Shah, Rajiv Ratn
This paper presents our submission to the SemEval 2020 - Task 10 on emphasis selection in written text. We approach this emphasis selection problem as a sequence labeling task where we represent the underlying text with various contextual embedding m
Externí odkaz:
http://arxiv.org/abs/2009.02619
Low-power chemical sensors deployed on mobile platforms make it possible to monitor pollutant concentrations across large urban areas. However, chemical sensors are prone to drift (e.g., aging, damage, poisoning) and have to be calibrated periodicall
Externí odkaz:
http://arxiv.org/abs/2006.12381
Autor:
Gautam, Akash, Mathur, Puneet, Gosangi, Rakesh, Mahata, Debanjan, Sawhney, Ramit, Shah, Rajiv Ratn
In this paper, we present a dataset containing 9,973 tweets related to the MeToo movement that were manually annotated for five different linguistic aspects: relevance, stance, hate speech, sarcasm, and dialogue acts. We present a detailed account of
Externí odkaz:
http://arxiv.org/abs/1912.06927
Autor:
Sahrawat, Dhruva, Mahata, Debanjan, Kulkarni, Mayank, Zhang, Haimin, Gosangi, Rakesh, Stent, Amanda, Sharma, Agniv, Kumar, Yaman, Shah, Rajiv Ratn, Zimmermann, Roger
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented using deep contextualized embeddings. We evaluate the proposed architect
Externí odkaz:
http://arxiv.org/abs/1910.08840
Autor:
Swaminathan, Avinash, Gupta, Raj Kuwar, Zhang, Haimin, Mahata, Debanjan, Gosangi, Rakesh, Shah, Rajiv Ratn
In this paper, we present a keyphrase generation approach using conditional Generative Adversarial Networks (GAN). In our GAN model, the generator outputs a sequence of keyphrases based on the title and abstract of a scientific article. The discrimin
Externí odkaz:
http://arxiv.org/abs/1909.12229
Autor:
İrsoy, Ozan, Gosangi, Rakesh, Zhang, Haimin, Wei, Mu-Hsin, Lund, Peter, Pappadopulo, Duccio, Fahy, Brendan, Nephytou, Neophytos, Ortiz, Camilo
Dialogue act (DA) classification has been studied for the past two decades and has several key applications such as workflow automation and conversation analytics. Researchers have used, to address this problem, various traditional machine learning m
Externí odkaz:
http://arxiv.org/abs/1908.01821
Autor:
Gosangi, Rakesh
Chemical sensors are generally used as one-dimensional devices, where one measures the sensor’s response at a fixed setting, e.g., infrared absorption at a specific wavelength, or conductivity of a solid-state sensor at a specific operating tempera
Externí odkaz:
http://hdl.handle.net/1969.1/151254
Publikováno v:
In Chemometrics and Intelligent Laboratory Systems 15 March 2014 132:91-102
