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Xinyu Qiu

2 accepted papers

2026

Unified Generation and Self-Verification for Vision-Language Models via Advantage Decoupled Preference Optimization

CVPR 2026

Parallel test-time scaling typically trains separate generation and verification models, incurring high training and inference costs. We propose Advantage Decoupled Preference Optimization (ADPO), a unified reinforcement learning framework that jointly learns answer generation and self-verification

Cited by 0SourcecodeScholar
2025

MuTIS: Enhancing Reasoning Efficiency through Multi Turn Intervention Sampling in Reinforcement Learning

EMNLP 2025

Recently, large reasoning models (LRMs) have demonstrated state-of-the-art performance across a wide range of benchmarks. However, a common challenge for these models is the “overthinking” problem, which leads to excessive reasoning steps and significant computational overhead. Furthermore, the issu