PPaperPicks

Chuchu Fan

Massachusetts Institute of Technology, MA, USA

20 papers at tracked venues · 11 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. Optimization of Multi-Agent Flying Sidekick Traveling Salesman Problem over Road Networks
  2. Code-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generation
  3. CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance
  4. Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
  5. HMARL-CBF - Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems
  6. Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools
  7. Neural Combinatorial Optimization for Time-Dependent Traveling Salesman Problem
  8. Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming
  9. Rare event modeling with self-regularized normalizing flows: what can we learn from a single failure?
  10. Reliable and Efficient Multi-Agent Coordination via Graph Neural Network Variational Autoencoders
  11. Scalable Surrogate Verification of Image-Based Neural Network Control Systems Using Composition and Unrolling
  12. Steering Large Language Models between Code Execution and Textual Reasoning
  13. TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matching
  14. AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers
  15. ConBaT: Control Barrier Transformer for Safe Robot Learning from Demonstrations
  16. Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller
  17. How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems
  18. PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling
  19. Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?
  20. Solving Minimum-Cost Reach Avoid using Reinforcement Learning