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pro vyhledávání: '"Siledar, Tejpalsingh"'
Autor:
Muddu, Sri Raghava, Rangaraju, Rupasai, Siledar, Tejpalsingh, Nath, Swaroop, Bhattacharyya, Pushpak, Nath, Swaprava, Banerjee, Suman, Patil, Amey, Chelliah, Muthusamy, Singh, Sudhanshu Shekhar, Garera, Nikesh
Opinion summarization in e-commerce encapsulates the collective views of numerous users about a product based on their reviews. Typically, a product on an e-commerce platform has thousands of reviews, each review comprising around 10-15 words. While
Externí odkaz:
http://arxiv.org/abs/2406.10886
Autor:
Siledar, Tejpalsingh, Rangaraju, Rupasai, Muddu, Sankara Sri Raghava Ravindra, Banerjee, Suman, Patil, Amey, Singh, Sudhanshu Shekhar, Chelliah, Muthusamy, Garera, Nikesh, Nath, Swaprava, Bhattacharyya, Pushpak
In e-commerce, opinion summarization is the process of summarizing the consensus opinions found in product reviews. However, the potential of additional sources such as product description and question-answers (QA) has been considered less often. Mor
Externí odkaz:
http://arxiv.org/abs/2404.05243
Autor:
Nath, Swaroop, Siledar, Tejpalsingh, Muddu, Sankara Sri Raghava Ravindra, Rangaraju, Rupasai, Khadilkar, Harshad, Bhattacharyya, Pushpak, Banerjee, Suman, Patil, Amey, Singh, Sudhanshu Shekhar, Chelliah, Muthusamy, Garera, Nikesh
Reinforcement Learning from Human Feedback (RLHF) has become a dominating strategy in aligning Language Models (LMs) with human values/goals. The key to the strategy is learning a reward model ($\varphi$), which can reflect the latent reward model of
Externí odkaz:
http://arxiv.org/abs/2402.15473
Autor:
Siledar, Tejpalsingh, Nath, Swaroop, Muddu, Sankara Sri Raghava Ravindra, Rangaraju, Rupasai, Nath, Swaprava, Bhattacharyya, Pushpak, Banerjee, Suman, Patil, Amey, Singh, Sudhanshu Shekhar, Chelliah, Muthusamy, Garera, Nikesh
Evaluation of opinion summaries using conventional reference-based metrics rarely provides a holistic evaluation and has been shown to have a relatively low correlation with human judgments. Recent studies suggest using Large Language Models (LLMs) a
Externí odkaz:
http://arxiv.org/abs/2402.11683
Hyperbole and metaphor are common in day-to-day communication (e.g., "I am in deep trouble": how does trouble have depth?), which makes their detection important, especially in a conversational AI setting. Existing approaches to automatically detect
Externí odkaz:
http://arxiv.org/abs/2305.17480