#reward optimization

try —

2 papers match

cs.LG2026

HARGO: Heterogeneity-Aware Reward-Guided Optimization for RL Post-Training of LLMs on HPC Tasks

Tiangang Li, Xiangbo Tian

The paper introduces HARGO, a reinforcement‑learning post‑training method that weights responses by confidence and reward contrast to better align large language models with divers…

#large language models#reinforcement learning#high-performance computing#reward optimization

cs.CV2026

MagicPrompt: Ultra-Lightweight Prompt Tuning for Video Generation

Yinhan Zhang, Dingwei Tan, Dinwei Tan +4

The paper introduces MagicPrompt, a lightweight method that uses attention-embedded soft prompts and dual-space reward feedback to fine‑tune large video diffusion models with less…

#video generation#diffusion models#prompt tuning#parameter-efficient fine-tuning