activity
20202026
most citedReinforcement Learning with External Knowledge by using Logical Neural Networks

8 citations · 8 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Memes-as-Replies: Can Models Select Humorous Manga Panel Responses?

Ryosuke Kohita, Seiichiro Yoshioka

Memes are a popular element of modern web communication, used not only as static artifacts but also as interactive replies within conversations. While computational research has fo…

cs.CL2025

Exploring Database Normalization Effects on SQL Generation

Ryosuke Kohita

Schema design, particularly normalization, is a critical yet often overlooked factor in natural language to SQL (NL2SQL) systems. Most prior research evaluates models on fixed sche…

cs.HC2025

System-driven Interactive Design Support for Cloud Architecture: A Qualitative User Experience Study with Novice Engineers

Ryosuke Kohita, Akira Kasuga

Cloud architecture design presents significant challenges due to the necessity of clarifying ambiguous requirements and systematically addressing complex trade-offs, especially for…

cs.SE2025

System-driven Cloud Architecture Design Support with Structured State Management and Guided Decision Assistance

Ryosuke Kohita, Akira Kasuga

Cloud architecture design is a complex process requiring both technical expertise and architectural knowledge to develop solutions from frequently ambiguous requirements. We presen…

cs.AI2021

LOA: Logical Optimal Actions for Text-based Interaction Games

Daiki Kimura, Subhajit Chaudhury, Masaki Ono +6

We present Logical Optimal Actions (LOA), an action decision architecture of reinforcement learning applications with a neuro-symbolic framework which is a combination of neural ne…

cs.AI2021★ 8 cited

Reinforcement Learning with External Knowledge by using Logical Neural Networks

Daiki Kimura, Subhajit Chaudhury, Akifumi Wachi +4

Conventional deep reinforcement learning methods are sample-inefficient and usually require a large number of training trials before convergence. Since such methods operate on an u…

cs.CL2020

Q-learning with Language Model for Edit-based Unsupervised Summarization

Ryosuke Kohita, Akifumi Wachi, Yang Zhao +1

Unsupervised methods are promising for abstractive text summarization in that the parallel corpora is not required. However, their performance is still far from being satisfied, th…