BETAC: Bidirectional Encoder Transformer for Assembly Code Function Name Recovery
Guillaume Breyton
Mohd Saqib
Philippe Charland
Recovering function names from stripped binaries is a crucial and time-consuming task for software reverse engineering’ particularly in en… (see more)hancing network reliability, resilience, and security. This paper tackles the challenge of recovering function names in stripped binaries, a fundamental step in reverse engineering. The absence of syntactic information and the possibility of different code producing identical behavior complicate this task. To overcome these challenges, we introduce a novel model, the Bidirectional Encoder Transformer for Assembly Code (BETAC), leveraging a transformer-based architecture known for effectively processing sequential data. BETAC utilizes self-attention mechanisms and feed-forward networks to discern complex relationships within assembly code for precise function name prediction. We evaluated BETAC against various existing encoder and decoder models in diverse binary datasets, including benign and malicious codes in multiple formats. Our model demonstrated superior performance over previous techniques in certain metrics and showed resilience against code obfuscation.
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Reinforcement
Yunzhen Feng
Pu Yang
Francois Charton
Julia Kempe
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Reinforcement
Yunzhen Feng
Pu Yang
Francois Charton
Julia Kempe
Bidirectional Generative Pre-training for Improving Time Series Representation Learning
Ziyang Song
Qincheng Lu
Mike He Zhu
Bio-Mechanical Poet: An Immersive Audiovisual Playground for Brain Signals and Generative AI.
Philipp Thölke
Antoine Bellemare Pépin
Yann Harel
François Lespinasse
Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers.
Xiuying Wei
Skander Moalla
Caglar Gulcehre
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities
Eslam G. Al-Sakkari
Ahmed Ragab
Daria C. Boffito
Mouloud Amazouz
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.
Eslam G. Al-Sakkari
Ahmed Ragab
Daria Camilla Boffito
Mouloud Amazouz
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.
Eslam G. Al-Sakkari
Ahmed Ragab
Daria Camilla Boffito
Mouloud Amazouz
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.
Eslam G. Al-Sakkari
Ahmed Ragab
Daria Camilla Boffito
Mouloud Amazouz
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.
Eslam G. Al-Sakkari
Ahmed Ragab
Daria Camilla Boffito
Mouloud Amazouz
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities.
Eslam G. Al-Sakkari
Ahmed Ragab
Daria Camilla Boffito
Mouloud Amazouz