2 papers
cs.LG2026
Off-Policy Learning with Limited Supply
Koichi Tanaka, Ren Kishimoto, Bushun Kawagishi +4
We study off-policy learning (OPL) in contextual bandits, which plays a key role in a wide range of real-world applications such as recommendation systems and online advertising. T…
cs.CV2026
SLVMEval: Synthetic Meta Evaluation Benchmark for Text-to-Long Video Generation
Ryosuke Matsuda, Keito Kudo, Haruto Yoshida +2
This paper proposes the synthetic long-video meta-evaluation (SLVMEval), a benchmark for meta-evaluating text-to-video (T2V) evaluation systems. The proposed SLVMEval benchmark foc…