1 citations · 1 across the 6 of their papers we have counts for
7 papers
Steepest Guidance: A Practical and Principled Approach to Inference-Time Alignment of Flow and Diffusion-based Models
Shokichi Takakura, Akifumi Wachi, Rei Higuchi +2
Inference-time alignment of flow and diffusion-based models is critical for achieving flexible generative modeling. Theoretically, Doob's -transform provides an elegant solution…
How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis
Rei Higuchi, Ryotaro Kawata, Akifumi Wachi +3
Reward modeling is not only a prediction problem: in KL-regularized policy optimization, the learned reward is exponentiated to define the deployed policy, so downstream value depe…
Inference-Aware Meta-Alignment of LLMs via Non-Linear GRPO
Shokichi Takakura, Akifumi Wachi, Rei Higuchi +2
Aligning large language models (LLMs) to diverse human preferences is fundamentally challenging since criteria can often conflict with each other. Inference-time alignment methods…
A Relative-Budget Theory for Reinforcement Learning with Verifiable Rewards in Large Language Model Reasoning
Akifumi Wachi, Hirota Kinoshita, Shokichi Takakura +2
Reinforcement learning (RL) is a dominant paradigm for improving the reasoning abilities of large language models, yet its effectiveness varies across tasks and compute budgets. We…
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
Shokichi Takakura, Taiji Suzuki
In this paper, we study the feature learning ability of two-layer neural networks in the mean-field regime through the lens of kernel methods. To focus on the dynamics of the kerne…
Approximation and Estimation Ability of Transformers for Sequence-to-Sequence Functions with Infinite Dimensional Input
Shokichi Takakura, Taiji Suzuki
Despite the great success of Transformer networks in various applications such as natural language processing and computer vision, their theoretical aspects are not well understood…
Structured Output Feedback Control for Linear Quadratic Regulator Using Policy Gradient Method
Shokichi Takakura, Kazuhiro Sato
We consider the static output feedback control for Linear Quadratic Regulator problems with structured constraints under the assumption that system parameters are unknown. To solve…