Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Sengupta, Shubhashis"'
Autor:
Joshi, Ratnesh Kumar, Priya, Priyanshu, Desai, Vishesh, Dudhate, Saurav, Senapati, Siddhant, Ekbal, Asif, Ramnani, Roshni, Maitra, Anutosh, Sengupta, Shubhashis
Given the advancements in conversational artificial intelligence, the evaluation and assessment of Large Language Models (LLMs) play a crucial role in ensuring optimal performance across various conversational tasks. In this paper, we present a compr
Externí odkaz:
http://arxiv.org/abs/2411.17204
Autor:
Gatti, Prajwal, Penamakuri, Abhirama Subramanyam, Teotia, Revant, Mishra, Anand, Sengupta, Shubhashis, Ramnani, Roshni
One characteristic that makes humans superior to modern artificially intelligent models is the ability to interpret images beyond what is visually apparent. Consider the following two natural language search queries - (i) "a queue of customers patien
Externí odkaz:
http://arxiv.org/abs/2210.08554
Autor:
Singh, Sandhya, Roy, Prapti, Sahoo, Nihar, Mallela, Niteesh, Gupta, Himanshu, Bhattacharyya, Pushpak, Savagaonkar, Milind, Nidhi, Ramnani, Roshni, Maitra, Anutosh, Sengupta, Shubhashis
Movies reflect society and also hold power to transform opinions. Social biases and stereotypes present in movies can cause extensive damage due to their reach. These biases are not always found to be the need of storyline but can creep in as the aut
Externí odkaz:
http://arxiv.org/abs/2205.15951
Knowledge Graphs (KG) act as a great tool for holding distilled information from large natural language text corpora. The problem of natural language querying over knowledge graphs is essential for the human consumption of this information. This prob
Externí odkaz:
http://arxiv.org/abs/2112.11070
Autor:
Sundriyal, Megha, Singh, Parantak, Akhtar, Md Shad, Sengupta, Shubhashis, Chakraborty, Tanmoy
The formulation of a claim rests at the core of argument mining. To demarcate between a claim and a non-claim is arduous for both humans and machines, owing to latent linguistic variance between the two and the inadequacy of extensive definition-base
Externí odkaz:
http://arxiv.org/abs/2108.08759
Autor:
Khetan, Vivek, M, Annervaz K, Wetherley, Erin, Eneva, Elena, Sengupta, Shubhashis, Fano, Andrew E.
The growing quantity and complexity of data pose challenges for humans to consume information and respond in a timely manner. For businesses in domains with rapidly changing rules and regulations, failure to identify changes can be costly. In contras
Externí odkaz:
http://arxiv.org/abs/2104.08936
Fake tweets are observed to be ever-increasing, demanding immediate countermeasures to combat their spread. During COVID-19, tweets with misinformation should be flagged and neutralized in their early stages to mitigate the damages. Most of the exist
Externí odkaz:
http://arxiv.org/abs/2104.05321
Autor:
Paka, William Scott, Bansal, Rachit, Kaushik, Abhay, Sengupta, Shubhashis, Chakraborty, Tanmoy
As the COVID-19 pandemic sweeps across the world, it has been accompanied by a tsunami of fake news and misinformation on social media. At the time when reliable information is vital for public health and safety, COVID-19 related fake news has been s
Externí odkaz:
http://arxiv.org/abs/2102.08924
Autor:
Gupta, Deepak, Pujari, Rajkumar, Ekbal, Asif, Bhattacharyya, Pushpak, Maitra, Anutosh, Jain, Tom, Sengupta, Shubhashis
In this paper, we propose a hybrid technique for semantic question matching. It uses our proposed two-layered taxonomy for English questions by augmenting state-of-the-art deep learning models with question classes obtained from a deep learning based
Externí odkaz:
http://arxiv.org/abs/2101.08201
Causality understanding between events is a critical natural language processing task that is helpful in many areas, including health care, business risk management and finance. On close examination, one can find a huge amount of textual content both
Externí odkaz:
http://arxiv.org/abs/2012.05453