Titlebook: Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy; Proceedings of the F Manoj Sahni,José M. Merigó,Rajkumar

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Nimrabanu Memon,Samir B. Patel,Dhruvesh P. Patelosition transcripts generally consist of data in the form of question-answer (QA) pairs. Accordingly, our automated system starts with pre-processing, and then transforms the QA pairs into a canonical form made up of declarative sentences. Classifying the declarative sentences that are generated, ac

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VEIL

從屬

Mansi Palav,Ruchi Telang Gode,S. V. S. S. N. V. G. Krishna Murthyrge language models (LLMs) in advancing the development of more reliable and contextually aware Legal NER systems for intricate legal texts. This work contributes to the broader goal of enhancing the accuracy and efficiency of information extraction in the legal domain, showcasing the transformative

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Kartikkumar Thakkar,Ammar Vhora,Pravin Kodgire,Surendra Singh Kachhwahan approach we also adapt for Task 2. To address Task 4, we employ an ensemble of LLMs’ predictions, adjudicated via majority voting and the Dawid-Skene label model. Our strategies take advantage of the strengths of each model, with prompting techniques and constraints applied to exploit ensemble adv

四溢

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Santosh Kumar Bharti,Reddy Naidu,Korra Sathya Babuer ambiguity, scoping islands and binding, crossover, topicalization, and inverse linking. Most of these analyses have not been attempted for ACG..AACG offers a different perspective on linguistic side-effects, demonstrating compositionality not just of meanings but of transformations.

Salivary-Gland

er ambiguity, scoping islands and binding, crossover, topicalization, and inverse linking. Most of these analyses have not been attempted for ACG..AACG offers a different perspective on linguistic side-effects, demonstrating compositionality not just of meanings but of transformations.

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2194-5357 Engineers (IEI) – Gujarat and Computer Society of India (CSI) – Ahmedabad. The book provides innovative works of researchers, academicians and students in the area of interdisciplinary mathematics, statistics, computational intelligence and renewable energy.978-981-15-9952-1978-981-15-9953-8Series ISSN 2194-5357 Series E-ISSN 2194-5365