1 citations · 1 across the 10 of their papers we have counts for
10 papers
CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting
Xiaoyu Tao, Mingyue Cheng, Bokai Pan +6
Time series forecasting is fundamental to decision-making in complex systems, where future dynamics are influenced not only by historical observations but also by evolving contextu…
EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments
Deyao Zhu, Xin Zhou, Shengling Qin +44
Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deployment remains far less unders…
Learning Agentic Time Series Forecasting via Trajectory Distillation and Memory-Based Reinforcement Learning
Xiaoyu Tao, Mingyue Cheng, Chuang Jiang +7
Recent agentic time series forecasting (TSF) approaches use large language models (LLMs) to autonomously orchestrate analytical and forecasting tools and reason about temporal patt…
SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarios
Tian Gao, Celine Tan, Catherine Glossop +8
A fundamental challenge in autonomous driving is the integration of high-level, semantic reasoning for long-tail events with low-level, reactive control for robust driving. While l…
AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning
Xiaoyu Tao, Yuchong Wu, Mingyue Cheng +2
Time series anomaly detection is critical in many real-world applications, where effective solutions must localize anomalous regions and support reliable decision-making under comp…
TimeSense:Making Large Language Models Proficient in Time-Series Analysis
Zhirui Zhang, Changhua Pei, Tianyi Gao +7
In the time-series domain, an increasing number of works combine text with temporal data to leverage the reasoning capabilities of large language models (LLMs) for various downstre…
AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Time Series Forecasting
Xiaohan Zhang, Tian Gao, Mingyue Cheng +5
Time series forecasting is typically treated as a single-pass numerical prediction task based on historical observations. However, real-world forecasting often requires expert-like…
Few-shot Policy (de)composition in Conversational Question Answering
Kyle Erwin, Guy Axelrod, Maria Chang +8
The task of policy compliance detection (PCD) is to determine if a scenario is in compliance with respect to a set of written policies. In a conversational setting, the results of…
Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
Max Sobol Mark, Tian Gao, Georgia Gabriela Sampaio +4
Recent advances in learning decision-making policies can largely be attributed to training expressive policy models, largely via imitation learning. While imitation learning discar…
PRIME: Scaffolding Manipulation Tasks with Behavior Primitives for Data-Efficient Imitation Learning
Tian Gao, Soroush Nasiriany, Huihan Liu +2
Imitation learning has shown great potential for enabling robots to acquire complex manipulation behaviors. However, these algorithms suffer from high sample complexity in long-hor…