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20242026
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cs.LG2026

Prefix-Denoising Consistency: Test-Time Verification for Diffusion Language Models

Yuki Ichihara, Naoto Iwase, Mohammad Atif Quamar +1

Diffusion Language Models (DLMs) have recently become increasingly competitive with autoregressive (AR) models, and even outperform them on certain tasks. Unlike AR models, DLMs pr…

cs.LG2026

Privileged Solutions or Context-Induced Teacher Behavior? Dissecting On-Policy Self-Distillation

Yuki Ichihara, Naoto Iwase, Mohammad Atif Quamar +1

On-Policy Self-Distillation (OPSD) is commonly interpreted as the transfer of privileged information: a teacher observes the verified solution to the target problem and supervises…

cs.LG2026

Consensus Group Relative Policy Optimization for Text Generation

Yuki Ichihara, Yuu Jinnai, Kaito Ariu +1

Many strong decoding methods for text generation follow a sample-and-rerank paradigm: they draw multiple candidates, score each under a utility (reward) function using consensus ac…

cs.LG2025

MO-GRPO: Mitigating Reward Hacking of Group Relative Policy Optimization on Multi-Objective Problems

Yuki Ichihara, Yuu Jinnai, Tetsuro Morimura +3

Group Relative Policy Optimization (GRPO) has been shown to be an effective algorithm when an accurate reward model is available. However, such a highly reliable reward model is no…

cs.LG2024

A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees

Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato +6

We study a primal-dual (PD) reinforcement learning (RL) algorithm for online constrained Markov decision processes (CMDPs). Despite its widespread practical use, the existing theor…