Published in ACL Findings, 2024
We present PIXAR, the first pixel-based autoregressive LLM that understands and generates text-in-images, reaching GPT-2–level performance without relying on symbolic tokenization.
Published in ACL, 2023
We propose simulating natural language feedback for interactive semantic parsing, enabling scalable training without costly human annotations and improving text-to-SQL error correction.
Published in SPIE, 2021
We present an attention-enhanced U-Net model integrating Squeeze-and-Excitation and CBAM modules to improve MRI brain tumor segmentation, delivered with an app featuring text-to-speech and chatbot support.