1 citations · 1 across the 4 of their papers we have counts for
8 papers
Ulysses: A Security Harness For Synthesizing Verifiable Web Exploits
Aditya Oke, André Vicente Duarte, Rui Melo +6
How can an AI agent automatically discover security vulnerabilities in any software repository? Existing approaches use LLMs to generate software vulnerability exploits. However, i…
Self-Evolving Static Analysis via LLM Pseudo-Labeling
Rui Melo, Andre Duarte, Aditya Oke +5
Security bugs often slip past static analysis not because they are impossible to detect, but because detection rules have not yet been written for the code in front of us. New fram…
ABSENTIA: Detecting Broken Access Control Vulnerabilities in Web Applications
André V. Duarte, Aditya Oke, Rui Melo +7
Broken access control, the failure of authorization, is one of the most prevalent web security risks. Unlike injection, a flow of untrusted input into a dangerous operation, author…
Searching for Synergy in Shared Workspace Human-AI Collaboration
Nachiket Kotalwar, Rohini Das, Carolyn Rose
Automated AI agents are increasingly capable, yet many scientific and professional tasks require human judgment and contextual expertise. We use simulated shared-workspace human-AI…
Hybrid-Gym: Training Coding Agents to Generalize Across Tasks
Yiqing Xie, Emmy Liu, Gaokai Zhang +7
When assessing the quality of coding agents, predominant benchmarks focus on solving single issues on GitHub, such as SWE-Bench. In contrast, in real use, these agents solve more v…
Inference-Time Personalized Alignment with a Few User Preference Queries
Victor-Alexandru Pădurean, Parameswaran Kamalaruban, Nachiket Kotalwar +2
We study the problem of aligning a generative model's response with a user's preferences. Recent works have proposed several different formulations for personalized alignment; howe…
Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback
Victor-Alexandru Pădurean, Tung Phung, Nachiket Kotalwar +4
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current a…
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation
Nachiket Kotalwar, Alkis Gotovos, Adish Singla
Generative AI and large language models hold great promise in enhancing programming education by generating individualized feedback and hints for learners. Recent works have primar…