Papers with feedback module
Backtranslation Feedback Improves User Confidence in MT, Not Quality (2021.naacl-main)
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Vilém Zouhar, Michal Novák, Matúš Žilinec, Ondřej Bojar, Mateo Obregón, Robin L. Hill, Frédéric Blain, Marina Fomicheva, Lucia Specia, Lisa Yankovskaya
| Challenge: | Inbound translation is a modern need for which the user experience has significant room for improvement, beyond the basic machine translation facility. |
| Approach: | They propose to provide cues that indicate the quality of MT output as well as suggest possible rephrasing of the source language. |
| Outcome: | The proposed feedback module increases user confidence in the produced translation, but not the objective quality. |
CASPER: Bridging Discrete and Continuous Prompt Optimization through Feedback-Guided Gradient Descent (2026.eacl-industry)
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| Challenge: | Existing pipelines for generative tasks require extensive manual effort and domain expertise to achieve task-optimal performance. |
| Approach: | They propose a framework bridging discrete and continuous prompt optimization through feedback-guided gradient descent in embedding space. |
| Outcome: | The proposed framework bridges discrete and continuous prompt optimization through feedback-guided gradient descent in embedding space. |