Can Language Models Replace Programmers for Coding? RepoCod Says 'Not Yet'. Shanchao Liang, Yiran Hu, Nan Jiang, and Lin Tan.

WAFFLE: Webpage Multi-Modal Model for Automated Front-End Development. Shanchao Liang, Nan Jiang, Shangshu Qian, and Lin Tan.

Challenges to Using Large Language Models in Code Generation and Repair. Liliana Pasquale, Antonino Sabetta, Marcelo d'Amorim, Péter Hegedüs, Mehdi Tarrit Mirakhorli, Hamed Okhravi, Mathias Payer, Awais Rashid, Joanna C. S. Santos, Jonathan M. Spring, Lin Tan, and Katja Tuma.

SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models. Yi Wu, Zikang Xiong, Yiran Hu, Shreyash Iyengar, Nan Jiang, Aniket Bera, Lin Tan, and Suresh Jagannathan. Best Paper Award Finalist!

D3: Differential Testing of Distributed Deep Learning with Model Generation. Jiannan Wang, Hung Viet Pham, Qi Li, Lin Tan, Yu Guo, Adnan Aziz, and Erik Meijer.

Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning. Nan Jiang, Chengxiao Wang, Kevin Liu, Xiangzhe Xu, Lin Tan, Xiangyu Zhang, and Petr Babkin. Acceptance Rate: 32.1% [Model]

Show Me Why It's Correct: Saving 1/3 of Debugging Time in Program Repair with Interactive Runtime Comparison. Ruixin Wang, Zhongkai Zhao, Le Fang, Nan Jiang, Yiling Lou, Lin Tan, and Tianyi Zhang.

How Effective are Large Language Models in Generating Software Specifications? Danning Xie, Byoungwoo Yoo, Nan Jiang, Mijung Kim, Lin Tan, Xiangyu Zhang, and Judy Lee Acceptance Rate: 23% (52/225)

LATTE: Improving Latex Recognition for Tables and Formulae with Iterative Refinement. Nan Jiang, Shanchao Liang, Chengxiao Wang, Jiannan Wang, and Lin Tan. Acceptance Rate: 23.4% [Data] [Poster]

Unleashing the Power of Generative Model in Recovering Variable Names from Stripped Binary. Xiangzhe Xu, Zhuo Zhang, Zian Su, Ziyang Huang, Shiwei Feng, Yapeng Ye, Nan Jiang, Danning Xie, Siyuan Cheng, Lin Tan, and Xiangyu Zhang.

ReSym: Harnessing LLMs to Recover Variable and Data Structure Symbols from Stripped Binaries. Danning Xie, Zhuo Zhang, Nan Jiang, Xiangzhe Xu, Lin Tan, and Xiangyu Zhang. Won Distinguished Paper Award! [Code & Data]

When Automated Program Repair Meets Regression Testing---An Extensive Study on 2 Million Patches. Yiling Lou, Jun Yang, Samuel Benton, Dan Hao, Lin Tan, Zhenpeng Chen, Lu Zhang, and Lingming Zhang.

CEDAR: Continuous Testing of Deep Learning Libraries. Danning Xie, Jiannan Wang, Hung Viet Pham, Lin Tan, Yu Guo, Adnan Aziz, and Erik Meijer. [Poster]

DisGUIDE: Disagreement-Guided Data-Free Model Extraction. (Oral Presentation) Jonathan Rosenthal, Eric Enouen, Hung Viet Pham, and Lin Tan. Acceptance Rate: 19.6% [Code & Data]