5 papers
Anon: Extrapolating Adaptivity Beyond SGD and Adam
Yiheng Zhang, Kaiyan Zhao, Shaowu Wu +5
Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However, they often generalize worse th…
EDT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation
Kaiyan Zhao, Borong Zhang, Yiming Wang +4
In reinforcement learning (RL) for robotic manipulation, the Decision Transformer (DT) has emerged as an effective framework for addressing long-horizon tasks. However, DT's perfor…
HVAdam: A Full-Dimension Adaptive Optimizer
Yiheng Zhang, Shaowu Wu, Yuanzhuo Xu +4
Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However, they often generalize worse th…
A Survey on Task Scheduling in Carbon-Aware Container Orchestration
Jialin Yang, Zainab Saad, Jiajun Wu +3
The soaring energy demands of large-scale software ecosystems and cloud data centers, accelerated by the intensive training and deployment of large language models, have driven ene…
Enhancing LLM Agents for Code Generation with Possibility and Pass-rate Prioritized Experience Replay
Yuyang Chen, Kaiyan Zhao, Yiming Wang +3
Nowadays transformer-based Large Language Models (LLM) for code generation tasks usually apply sampling and filtering pipelines. Due to the sparse reward problem in code generation…