Exploring Security Vulnerabilities in Competitive Programming: An Empirical Study. - Debeshee Das; Noble Saji Mathews; Sridhar Chimalakonda (EASE, 2022)

The Landscape of Source Code Representation Learning in AI-Driven Software Engineering Tasks. - Sridhar Chimalakonda; Debeshee Das; Alex Mathai; Srikanth Tamilselvam; Atul Kumar 002 (ICSE Companion, 2023)

COMEX: A Tool for Generating Customized Source Code Representations. - Debeshee Das; Noble Saji Mathews; Alex Mathai; Srikanth Tamilselvam; Kranthi Sedamaki; Sridhar Chimalakonda; Atul Kumar 002 (ASE, 2023)

Blind Baselines Beat Membership Inference Attacks for Foundation Models. - Debeshee Das; Jie Zhang 107; Florian Tramèr (CoRR, 2024)

Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data. - Jie Zhang 107; Debeshee Das; Gautam Kamath 001; Florian Tramèr (CoRR, 2024)

CodeSAM: Source Code Representation Learning by Infusing Self-Attention with Multi-Code-View Graphs. - Alex Mathai; Kranthi Sedamaki; Debeshee Das; Noble Saji Mathews; Srikanth Tamilselvam; Sridhar Chimalakonda; Atul Kumar 002 (CoRR, 2024)

Position: Membership Inference Attacks Cannot Prove That a Model was Trained on Your Data. - Jie Zhang 107; Debeshee Das; Gautam Kamath 001; Florian Tramèr (SaTML, 2025)

Blind Baselines Beat Membership Inference Attacks for Foundation Models. - Debeshee Das; Jie Zhang; Florian Trantèr (SP (Workshops), 2025)