5 citations · 8 across the 11 of their papers we have counts for
11 papers
From 'What' to 'How' and 'Why': Sharing LLM-Generated Retrospective Summaries of Older Adults' Passive Tracking Data with Remote Family Members
Jiachen Li, Reina Szeyi Chan, Akshat Choube +3
With the growing prevalence of modern ubiquitous computing technologies, multi-modal tracking systems hold promise for providing timely awareness and reassurance to stakeholders su…
VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting
Xudong Zhang, Jierui Lei, Jiacheng Li +3
Out of distribution (OOD) events in multivariate time series forecasting are rare but often dominate real world risk, making average case forecasting insufficient for reliable depl…
Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support
Siyan Li, Zehao Wang, Jiachen Li +3
Transportation systems management and operations (TSMO) increasingly depends on timely interpretation of heterogeneous data, from various sensor streams, incident reports, traveler…
Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving
Bernard Lange, Masha Itkina, Jiachen Li +1
Environment prediction frameworks are critical for the safe navigation of autonomous vehicles (AVs) in dynamic settings. LiDAR-generated occupancy grid maps (L-OGMs) offer a robust…
Adaptive Prediction Ensemble: Improving Out-of-Distribution Generalization of Motion Forecasting
Jinning Li, Jiachen Li, Sangjae Bae +1
Deep learning-based trajectory prediction models for autonomous driving often struggle with generalization to out-of-distribution (OOD) scenarios, sometimes performing worse than s…
Graph Q-Learning for Combinatorial Optimization
Victoria M. Dax, Jiachen Li, Kevin Leahy +1
Graph-structured data is ubiquitous throughout natural and social sciences, and Graph Neural Networks (GNNs) have recently been shown to be effective at solving prediction and infe…
Disentangled Neural Relational Inference for Interpretable Motion Prediction
Victoria M. Dax, Jiachen Li, Enna Sachdeva +2
Effective interaction modeling and behavior prediction of dynamic agents play a significant role in interactive motion planning for autonomous robots. Although existing methods hav…
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
Jiachen Li, Chuanbo Hua, Jianpeng Yao +4
Social robot navigation can be helpful in various contexts of daily life but requires safe human-robot interactions and efficient trajectory planning. While modeling pairwise relat…
Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimation
Jiachen Li, David Isele, Kanghoon Lee +3
Deep reinforcement learning (DRL) provides a promising way for intelligent agents (e.g., autonomous vehicles) to learn to navigate complex scenarios. However, DRL with neural netwo…
Predicting Future Spatiotemporal Occupancy Grids with Semantics for Autonomous Driving
Maneekwan Toyungyernsub, Esen Yel, Jiachen Li +1
For autonomous vehicles to proactively plan safe trajectories and make informed decisions, they must be able to predict the future occupancy states of the local environment. Howeve…
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning
Enna Sachdeva, Nakul Agarwal, Suhas Chundi +5
The widespread adoption of commercial autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) may largely depend on their acceptance by society, for which their per…