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Tejpalsingh Siledar

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CL3
ORCID 0000-0003-4474-6851

identity via Semantic Scholar / OpenAlex

most citedLeveraging Domain Knowledge for Efficient Reward Modelling in RLHF: A Case-Study in E-Commerce Opinion Summarization

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CL2024

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…

cs.CL2024★ 1 cited

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…

cs.CL2023

A Match Made in Heaven: A Multi-task Framework for Hyperbole and Metaphor Detection

Naveen Badathala, Abisek Rajakumar Kalarani, Tejpalsingh Siledar +1

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 c…

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