Search Results for author:
Found 3 papers, 2 papers with code
Understanding Impact of Human Feedback via Influence Functions
By quantifying the impact of human feedback on reward models, we believe that influence functions can enhance feedback interpretability and contribute to scalable oversight in RLHF, helping labelers provide more accurate and consistent feedback.
Benchmarking Mobile Device Control Agents across Diverse Configurations
In this work, we introduce B-MoCA: a novel benchmark with interactive environments for evaluating and developing mobile device control agents.
ComGAN: Toward GANs Exploiting Multiple Samples
In this paper, we propose ComGAN(ComparativeGAN) which allows the generator in GANs to refer to the semantics of comparative samples(e. g. real data) by comparison.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
