Real-time distributed algorithms for nonconvex optimal power flow. - Yuejiang Liu; Jean-Hubert Hours; Giorgos Stathopoulos; Colin N. Jones (ACC, 2017)

Map-based Deep Imitation Learning for Obstacle Avoidance. - Yuejiang Liu; An Xu; Zichong Chen (IROS, 2018)

Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning. - Changan Chen; Yuejiang Liu; Sven Kreiss; Alexandre Alahi (ICRA, 2019)

Collaborative GAN Sampling. - Yuejiang Liu; Parth Kothari; Alexandre Alahi (CoRR, 2019)

Collaborative Sampling in Generative Adversarial Networks. - Yuejiang Liu; Parth Kothari; Alexandre Alahi (AAAI, 2020)

Social NCE: Contrastive Learning of Socially-aware Motion Representations. - Yuejiang Liu; Qi Yan 007; Alexandre Alahi (ICCV, 2021)

Learning Decoupled Representations for Human Pose Forecasting. - Behnam Parsaeifard; Saeed Saadatnejad; Yuejiang Liu; Taylor Mordan; Alexandre Alahi (ICCVW, 2021)

TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive? - Yuejiang Liu; Parth Kothari; Bastien van Delft; Baptiste Bellot-Gurlet; Taylor Mordan; Alexandre Alahi (NeurIPS, 2021)

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting. - Parth Kothari; Danya Li; Yuejiang Liu; Alexandre Alahi (CoRL, 2022)

Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective. - Yuejiang Liu; Riccardo Cadei; Jonas Schweizer; Sherwin Bahmani; Alexandre Alahi (CVPR, 2022)

Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. - Yuejiang Liu; Alexandre Alahi; Chris Russell 001; Max Horn; Dominik Zietlow; Bernhard Schölkopf; Francesco Locatello (CLeaR, 2023)

On Pitfalls of Test-Time Adaptation. - Hao Zhao; Yuejiang Liu; Alexandre Alahi; Tao Lin (ICML, 2023)

Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts. - Yuejiang Liu; Alexandre Alahi (CoRR, 2024)

Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models. - Jifeng Wang; Kaouther Messaoud; Yuejiang Liu; Juergen Gall; Alexandre Alahi (CoRR, 2024)

Bidirectional Decoding: Improving Action Chunking via Closed-Loop Resampling. - Yuejiang Liu; Jubayer Ibn Hamid; Annie Xie; Yoonho Lee 001; Maximilian Du; Chelsea Finn (CoRR, 2024)

TAROT: Targeted Data Selection via Optimal Transport. - Lan Feng; Fan Nie; Yuejiang Liu; Alexandre Alahi (CoRR, 2024)

Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations. - Ahmad Rahimi; Po-Chien Luan; Yuejiang Liu; Frano Rajic; Alexandre Alahi (CVPR, 2025)

Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling. - Yuejiang Liu; Jubayer Ibn Hamid; Annie Xie; Yoonho Lee 001; Max Du; Chelsea Finn (ICLR, 2025)

Curating Demonstrations using Online Experience. - Annie S. Chen; Alec M. Lessing; Yuejiang Liu; Chelsea Finn (CoRR, 2025)

Learning Long-Context Diffusion Policies via Past-Token Prediction. - Marcel Torne; Andy Tang; Yuejiang Liu; Chelsea Finn (CoRR, 2025)