5 papers
TANDEM: Bi-Level Data Mixture Optimization with Twin Networks
Jiaxing Wang, Deping Xiang, Jin Xu +9
The capabilities of large language models (LLMs) significantly depend on training data drawn from various domains. Optimizing domain-specific mixture ratios can be modeled as a bi-…
Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning
Yu Li, Mingyang Yi, Xiuyu Li +6
Agentic Reinforcement Learning (ARL) trains large language models to interleave reasoning with external tool execution to solve complex tasks. Most existing ARL methods train a sin…
ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment
Xiuyu Li, Jinkai Zhang, Mingyang Yi +4
Reinforcement Learning (RL) post-training alignment for language models is effective, but also costly and unstable in practice, owing to its complicated training process. To addres…
Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images
Haoyang Jiang, Mingyang Yi, Shaolei Zhang +4
Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. Among existing approaches, re…
OFA-Diffusion Compression: Compressing Diffusion Model in One-Shot Manner
Haoyang Jiang, Zekun Wang, Mingyang Yi +6
The Diffusion Probabilistic Model (DPM) achieves remarkable performance in image generation, while its increasing parameter size and computational overhead hinder its deployment in…