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Jiayi Wei

7 accepted papers

2025

cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax Tree

EMNLP 2025

Retrieval-Augmented Generation (RAG) has become essential for large-scale code generation, grounding predictions in external code corpora to improve factuality. However, a critical yet underexplored aspect of RAG pipelines is chunking—the process of dividing documents into retrievable units. Existin

2024

Programmatic Imitation Learning From Unlabeled and Noisy Demonstrations

RA-L 2024

Imitation Learning (IL) is a promising paradigm for teaching robots to perform novel tasks using demonstrations. Most existing approaches for IL utilize neural networks (NN), however, these methods suffer from several well-known limitations: they 1) require large amounts of training data, 2) are har

Cited by 4SourcecodeScholar
2022

STEADY: Simultaneous State Estimation and Dynamics Learning from Indirect Observations

IROS 2022poster

Accurate kinodynamic models play a crucial role in many robotics applications such as off-road navigation and high-speed driving. Many state-of-the-art approaches for learning stochastic kinodynamic models, however, require precise measurements of robot states as labeled input/output examples, which…

Cited by 5SourcecodeScholar
2021

OneVision: Centralized to Distributed Controller Synthesis with Delay Compensation

IROS 2021poster

We propose a new algorithm to simplify the controller development for distributed robotic systems subject to external observations, disturbances, and communication delays. Unlike prior approaches that propose specialized solutions to handling communication latency for specific robotic applications,…

Cited by 5SourcecodeScholar
2020

LambdaNet: Probabilistic Type Inference using Graph Neural Networks

ICLR 2020poster

As gradual typing becomes increasingly popular in languages like Python and TypeScript, there is a growing need to infer type annotations automatically. While type annotations help with tasks like code completion and static error catching, these annotations cannot be fully inferred by compilers and…

Cited by 141SourcecodeScholar