4 citations · 5 across the 6 of their papers we have counts for
6 papers
Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification
Francisco Costa, Ismael Medeiros, Leandro Oliveira +5
The widespread use of smartphones in daily life has raised concerns about privacy and security among researchers and practitioners. Privacy issues are generally highly prevalent in…
Problem Solving Through Human-AI Preference-Based Cooperation
Subhabrata Dutta, Timo Kaufmann, Goran Glavaš +7
While there is a widespread belief that artificial general intelligence (AGI) -- or even superhuman AI -- is imminent, complex problems in expert domains are far from being solved.…
A Critical Study of What Code-LLMs (Do Not) Learn
Abhinav Anand, Shweta Verma, Krishna Narasimhan +1
Large Language Models trained on code corpora (code-LLMs) have demonstrated impressive performance in various coding assistance tasks. However, despite their increased size and tra…
Supporting Error Chains in Static Analysis for Precise Evaluation Results and Enhanced Usability
Anna-Katharina Wickert, Michael Schlichtig, Marvin Vogel +3
Context: Static analyses are well-established to aid in understanding bugs or vulnerabilities during the development process or in large-scale studies. A low false-positive rate is…
Amplifying Exploration in Monte-Carlo Tree Search by Focusing on the Unknown
Cedric Derstroff, Jannis Brugger, Jannis Blüml +3
Monte-Carlo tree search (MCTS) is an effective anytime algorithm with a vast amount of applications. It strategically allocates computational resources to focus on promising segmen…
Towards Trustworthy AI Software Development Assistance
Daniel Maninger, Krishna Narasimhan, Mira Mezini
It is expected that in the near future, AI software development assistants will play an important role in the software industry. However, current software development assistants te…