3 citations · 4 across the 3 of their papers we have counts for
6 papers · 1 filter
Distilling Opinions at Scale: Incremental Opinion Summarization using XL-OPSUMM
Sri Raghava Muddu, Rupasai Rangaraju, Tejpalsingh Siledar +8
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 t…
Product Description and QA Assisted Self-Supervised Opinion Summarization
Tejpalsingh Siledar, Rupasai Rangaraju, Sankara Sri Raghava Ravindra Muddu +7
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 des…
Leveraging Domain Knowledge for Efficient Reward Modelling in RLHF: A Case-Study in E-Commerce Opinion Summarization
Swaroop Nath, Tejpalsingh Siledar, Sankara Sri Raghava Ravindra Muddu +8
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…
Reference Free Domain Adaptation for Translation of Noisy Questions with Question Specific Rewards
Baban Gain, Ramakrishna Appicharla, Soumya Chennabasavaraj +3
Community Question-Answering (CQA) portals serve as a valuable tool for helping users within an organization. However, making them accessible to non-English-speaking users continue…
Study of Encoder-Decoder Architectures for Code-Mix Search Query Translation
Mandar Kulkarni, Soumya Chennabasavaraj, Nikesh Garera
With the broad reach of the internet and smartphones, e-commerce platforms have an increasingly diversified user base. Since native language users are not conversant in English, th…
Vernacular Search Query Translation with Unsupervised Domain Adaptation
Mandar Kulkarni, Nikesh Garera
With the democratization of e-commerce platforms, an increasingly diversified user base is opting to shop online. To provide a comfortable and reliable shopping experience, it's im…