5 papers
QoS-QoE Translation with Large Language Model
Yingjie Yu, Mingyuan Wu, Ahmadreza Eslaminia +3
QoS-QoE translation is a fundamental problem in multimedia systems because it characterizes how measurable system and network conditions affect user-perceived experience. Although…
OPPO: Accelerating PPO-based RLHF via Pipeline Overlap
Kaizhuo Yan, Yingjie Yu, Yifan Yu +2
Proximal Policy Optimization (PPO)-based reinforcement learning from human feedback (RLHF) is a widely adopted paradigm for aligning large language models (LLMs) with human prefere…
VTool-R1: VLMs Learn to Think with Images via Reinforcement Learning on Multimodal Tool Use
Mingyuan Wu, Jingcheng Yang, Jize Jiang +6
Reinforcement Learning Finetuning (RFT) has significantly advanced the reasoning capabilities of large language models (LLMs) by enabling long chains of thought, self-correction, a…
Aha Moment Revisited: Are VLMs Truly Capable of Self Verification in Inference-time Scaling?
Mingyuan Wu, Meitang Li, Jingcheng Yang +6
Inference time techniques such as decoding time scaling and self refinement have been shown to substantially improve mathematical reasoning in large language models (LLMs), largely…
Multilayer Dataflow: Orchestrate Butterfly Sparsity to Accelerate Attention Computation
Haibin Wu, Wenming Li, Kai Yan +9
Recent neural networks (NNs) with self-attention exhibit competitiveness across different AI domains, but the essential attention mechanism brings massive computation and memory de…