activity
20242026
collaborators

7 papers

cs.AI2026

GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training

Yuan Cao, Dezhi Ran, Mengzhou Wu +9

Post-training GUI agents in interactive environments is critical for developing generalization and long-horizon planning capabilities. However, training on real-world applications…

cs.LG2025

KernelBand: Steering LLM-based Kernel Optimization via Hardware-Aware Multi-Armed Bandits

Dezhi Ran, Shuxiao Xie, Mingfang Ji +9

High-performance GPU kernels are critical for efficient LLM serving, yet their optimization remains a bottleneck requiring deep system expertise. While code LLMs show promise in ge…

cs.SE2025

AppForge: From Assistant to Independent Developer -- Are GPTs Ready for Software Development?

Dezhi Ran, Yuan Cao, Mengzhou Wu +10

Large language models (LLMs) have demonstrated remarkable capability in function-level code generation tasks. Unlike isolated functions, real-world applications demand reasoning ov…

cs.CV2025

LLIA -- Enabling Low-Latency Interactive Avatars: Real-Time Audio-Driven Portrait Video Generation with Diffusion Models

Haojie Yu, Zhaonian Wang, Yihan Pan +7

Diffusion-based models have gained wide adoption in the virtual human generation due to their outstanding expressiveness. However, their substantial computational requirements have…

cs.SE2025

Beyond Pass or Fail: Multi-Dimensional Benchmarking of Foundation Models for Goal-based Mobile UI Navigation

Dezhi Ran, Mengzhou Wu, Hao Yu +15

Recent advances of foundation models (FMs) have made navigating mobile applications (apps) based on high-level goal instructions within reach, with significant industrial applicati…

cs.SE2025

DeCon: Detecting Incorrect Assertions via Postconditions Generated by a Large Language Model

Hao Yu, Tianyu Chen, Jiaming Huang +8

Recently, given the docstring for the target problem and the target function signature, large language models (LLMs) have been used not only to generate source code, but also to ge…

cs.SE2024

Automated Proof Generation for Rust Code via Self-Evolution

Tianyu Chen, Shuai Lu, Shan Lu +11

Ensuring correctness is crucial for code generation. Formal verification offers a definitive assurance of correctness, but demands substantial human effort in proof construction an…