7 papers
Simply Stabilizing the Loop via Fully Looped Transformer
Rao Fu, Zixuan Yang, Jiankun Zhang +4
Scaling model performance typically requires increasing model size. Looped Transformer offers a compelling alternative by iteratively reusing the same Transformer blocks, trading a…
CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment
Siyuan Guo, Yali Du, Hechang Chen +2
Large language models (LLMs) have become a central foundation of modern artificial intelligence, yet their lifecycle remains constrained by a rigid separation between training and…
A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning
Siyuan Guo, Yanchao Sun, Jifeng Hu +5
Offline reinforcement learning (RL) provides a promising solution to learning an agent fully relying on a data-driven paradigm. However, constrained by the limited quality of the o…
Optimizing Case-Based Reasoning System for Functional Test Script Generation with Large Language Models
Siyuan Guo, Huiwu Liu, Xiaolong Chen +6
In this work, we explore the potential of large language models (LLMs) for generating functional test scripts, which necessitates understanding the dynamically evolving code struct…
Decision Flow Policy Optimization
Jifeng Hu, Sili Huang, Siyuan Guo +6
In recent years, generative models have shown remarkable capabilities across diverse fields, including images, videos, language, and decision-making. By applying powerful generativ…
Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning
Jifeng Hu, Sili Huang, Zhejian Yang +6
Conditional decision generation with diffusion models has shown powerful competitiveness in reinforcement learning (RL). Recent studies reveal the relation between energy-function-…