3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 3 cited
Reviewer2: Optimizing Review Generation Through Prompt Generation
Zhaolin Gao, Kianté Brantley, Thorsten Joachims
Recent developments in LLMs offer new opportunities for assisting authors in improving their work. In this paper, we envision a use case where authors can receive LLM-generated rev…
cs.IR2018★ 2 cited
A General Framework for Counterfactual Learning-to-Rank
Aman Agarwal, Kenta Takatsu, Ivan Zaitsev +1
Implicit feedback (e.g., click, dwell time) is an attractive source of training data for Learning-to-Rank, but its naive use leads to learning results that are distorted by present…