2 citations · 4 across the 8 of their papers we have counts for
9 papers
LLM Agents for Automated Post-Training via Structured Recipe Optimization
Ruohong Liu, Bohan Tang, Lekang Jiang +2
Automated post-training transforms pre-trained large language models (LLMs) into models capable of handling diverse domains by automatically constructing and optimizing a recipe of…
BEAVER: Building Environments with Assessable Variation for Evaluating Multi-Objective Reinforcement Learning
Ruohong Liu, Jack Umenberger, Yize Chen
Recent years have seen significant advancements in designing reinforcement learning (RL)-based agents for building energy management. While individual success is observed in simula…
Hierarchical Learning-based Graph Partition for Large-scale Vehicle Routing Problems
Yuxin Pan, Ruohong Liu, Yize Chen +2
Neural solvers based on the divide-and-conquer approach for Vehicle Routing Problems (VRPs) in general, and capacitated VRP (CVRP) in particular, integrates the global partition of…
C-MORL: Multi-Objective Reinforcement Learning through Efficient Discovery of Pareto Front
Ruohong Liu, Yuxin Pan, Linjie Xu +4
Multi-objective reinforcement learning (MORL) excels at handling rapidly changing preferences in tasks that involve multiple criteria, even for unseen preferences. However, previou…
Learning and Optimization for Price-based Demand Response of Electric Vehicle Charging
Chengyang Gu, Yuxin Pan, Ruohong Liu +1
In the context of charging electric vehicles (EVs), the price-based demand response (PBDR) is becoming increasingly significant for charging load management. Such response usually…
Large Foundation Models for Power Systems
Chenghao Huang, Siyang Li, Ruohong Liu +2
Foundation models, such as Large Language Models (LLMs), can respond to a wide range of format-free queries without any task-specific data collection or model training, creating va…
Laxity-Aware Scalable Reinforcement Learning for HVAC Control
Ruohong Liu, Yuxin Pan, Yize Chen
Demand flexibility plays a vital role in maintaining grid balance, reducing peak demand, and saving customers' energy bills. Given their highly shiftable load and significant contr…
Learning a Multi-Agent Controller for Shared Energy Storage System
Ruohong Liu, Yize Chen
Deployment of shared energy storage systems (SESS) allows users to use the stored energy to meet their own energy demands while saving energy costs without installing private energ…
Learning Task-Aware Energy Disaggregation: a Federated Approach
Ruohong Liu, Yize Chen
We consider the problem of learning the energy disaggregation signals for residential load data. Such task is referred as non-intrusive load monitoring (NILM), and in order to find…