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Found 8 papers, 5 papers with code
Leveraging Domain Knowledge for Efficient Reward Modelling in RLHF: A Case-Study in E-Commerce Opinion Summarization
While this strategy has proven to be effective, the training methodology requires a lot of human preference annotation (usually of the order of tens of thousands) to train {$\varphi$}.
An Application to Generate Style Guided Compatible Outfit
Fashion recommendation has witnessed a phenomenal growth of research, particularly in the domains of shop-the-look, contextaware outfit creation, personalizing outfit creation etc.
One Prompt To Rule Them All: LLMs for Opinion Summary Evaluation
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.
Learning Cross-Task Attribute - Attribute Similarity for Multi-task Attribute-Value Extraction
We perform detailed experiments to show that our method indeed increases the macro-F1 scores for attribute value extraction in general, and for labels with low training data in particular.
Recommendation of Compatible Outfits Conditioned on Style
Recommendation in the fashion domain has seen a recent surge in research in various areas, for example, shop-the-look, context-aware outfit creation, personalizing outfit creation, etc.
Low Resource Chat Translation: A Benchmark for Hindi–English Language Pair
Chatbots are used in various sectors such as banking, healthcare, e-commerce, etc, and are mainly available in English.
Reference Free Domain Adaptation for Translation of Noisy Questions with Question Specific Rewards
Translating questions using Neural Machine Translation (NMT) poses more challenges, especially in noisy environments, where the grammatical correctness of the questions is not monitored.
Product Description and QA Assisted Self-Supervised Opinion Summarization
For evaluation, due to the unavailability of test sets with additional sources, we extend the Amazon, Oposum+, and Flipkart test sets and leverage ChatGPT to annotate summaries.
