42 citations · 45 across the 20 of their papers we have counts for
5 papers · 1 filter
Model-Based Minimum Bayes Risk Decoding for Text Generation
Yuu Jinnai, Tetsuro Morimura, Ukyo Honda +2
Minimum Bayes Risk (MBR) decoding has been shown to be a powerful alternative to beam search decoding in a variety of text generation tasks. MBR decoding selects a hypothesis from…
Policy Gradient with Kernel Quadrature
Satoshi Hayakawa, Tetsuro Morimura
Reward evaluation of episodes becomes a bottleneck in a broad range of reinforcement learning tasks. Our aim in this paper is to select a small but representative subset of a large…
On the Depth between Beam Search and Exhaustive Search for Text Generation
Yuu Jinnai, Tetsuro Morimura, Ukyo Honda
Beam search and exhaustive search are two extreme ends of text decoding algorithms with respect to the search depth. Beam search is limited in both search width and depth, whereas…
Why Guided Dialog Policy Learning performs well? Understanding the role of adversarial learning and its alternative
Sho Shimoyama, Tetsuro Morimura, Kenshi Abe +6
Dialog policies, which determine a system's action based on the current state at each dialog turn, are crucial to the success of the dialog. In recent years, reinforcement learning…
Safe Collaborative Filtering
Riku Togashi, Tatsushi Oka, Naoto Ohsaka +1
Excellent tail performance is crucial for modern machine learning tasks, such as algorithmic fairness, class imbalance, and risk-sensitive decision making, as it ensures the effect…