TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation. - Li Ding 010; Chenliang Xu (CoRR, 2017)

MIT Autonomous Vehicle Technology Study: Large-Scale Deep Learning Based Analysis of Driver Behavior and Interaction with Automation. - Lex Fridman 001; Daniel E. Brown; Michael Glazer; William Angell; Spencer Dodd; Benedikt Jenik; Jack Terwilliger; Julia Kindelsberger; Li Ding 010; Sean Seaman; Hillary Abraham; Alea Mehler; et al. (CoRR, 2017)

Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment. - Li Ding 010; Chenliang Xu (CVPR, 2018)

Arguing Machines: Human Supervision of Black Box AI Systems That Make Life-Critical Decisions. - Lex Fridman 001; Li Ding 010; Benedikt Jenik; Bryan Reimer (CVPR Workshops, 2019)

MIT Advanced Vehicle Technology Study: Large-Scale Naturalistic Driving Study of Driver Behavior and Interaction With Automation. - Lex Fridman 001; Daniel E. Brown; Michael Glazer; William Angell; Spencer Dodd; Benedikt Jenik; Jack Terwilliger; Aleksandr Patsekin; Julia Kindelsberger; Li Ding 010; Sean Seaman; Alea Mehler; et al. (IEEE Access, 2019)

Object as Distribution. - Li Ding 010; Lex Fridman 001 (CoRR, 2019)

MIT-AVT Clustered Driving Scene Dataset: Evaluating Perception Systems in Real-World Naturalistic Driving Scenarios. - Li Ding 010; Michael Glazer; Meng Wang; Bruce Mehler; Bryan Reimer; Lex Fridman 001 (IV, 2020)

MIT DriveSeg (Semi-auto) Dataset. - Li Ding 010; Michael Glazer; Jack Terwilliger; Bryan Reimer; Lex Fridman 001 (IEEE DataPort, 2020)

MIT DriveSeg (Manual) Dataset. - Li Ding 010; Jack Terwilliger; Rini Sherony; Bryan Reimer; Lex Fridman 001 (IEEE DataPort, 2020)

Evolving neural selection with adaptive regularization. - Li Ding 010; Lee Spector (GECCO Companion, 2021)

Perceptual Evaluation of Driving Scene Segmentation. - Li Ding 010; Rini Sherony; Bruce Mehler; Bryan Reimer (IV, 2021)

Going faster and hence further with lexicase selection. - Li Ding 010; Ryan Boldi; Thomas Helmuth; Lee Spector (GECCO Companion, 2022)

Lexicase selection at scale. - Li Ding 010; Ryan Boldi; Thomas Helmuth; Lee Spector (GECCO Companion, 2022)

Evolutionary quantum architecture search for parametrized quantum circuits. - Li Ding 010; Lee Spector (GECCO Companion, 2022)

Optimizing Neural Networks with Gradient Lexicase Selection. - Li Ding 010; Lee Spector (ICLR, 2022)

Value of Temporal Dynamics Information in Driving Scene Segmentation. - Li Ding 010; Jack Terwilliger; Rini Sherony; Bryan Reimer; Lex Fridman 001 (IEEE Trans. Intell. Veh., 2022)

Probabilistic Lexicase Selection. - Li Ding 010; Edward R. Pantridge; Lee Spector (GECCO, 2023)

Particularity. - Lee Spector; Li Ding 010; Ryan Boldi (GPTP, 2023)

Quality Diversity through Human Feedback. - Li Ding 010; Jenny Zhang; Jeff Clune; Lee Spector; Joel Lehman (CoRR, 2023)

Objectives Are All You Need: Solving Deceptive Problems Without Explicit Diversity Maintenance. - Ryan Boldi; Li Ding 010; Lee Spector (CoRR, 2023)

Multi-Objective Evolutionary Architecture Search for Parameterized Quantum Circuits. - Li Ding 010; Lee Spector (Entropy, 2023)

CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild. - Li Ding 010; Jack Terwilliger; Aishni Parab; Meng Wang; Lex Fridman 001; Bruce Mehler; Bryan Reimer (ACM Trans. Comput. Hum. Interact., 2023)

DALex: Lexicase-Like Selection via Diverse Aggregation. - Andrew Ni; Li Ding 010; Lee Spector (EuroGP, 2024)

Solving Deceptive Problems Without Explicit Diversity Maintenance. - Ryan Boldi; Li Ding 010; Lee Spector (GECCO Companion, 2024)

Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization. - Li Ding 010; Jenny Zhang; Jeff Clune; Lee Spector; Joel Lehman (ICML, 2024)

Pareto-Optimal Learning from Preferences with Hidden Context. - Ryan Boldi; Li Ding 010; Lee Spector; Scott Niekum (CoRR, 2024)