We're excited to invite you to attend DLSP 2025, co-located with IEEE S&P on May 15! dlsp2025.ieee-security.org
Themes:
+ Security & Privacy for ML
+ ML for Security & Privacy
Invited speakers include:
+ David Wagner (UC Berkeley)
+ Yuan Tian (UCLA)
+ Anoop Singhal (NIST)
More…
📢 Excited to share our new paper: Challenges and Paths Towards AI for SWE
We discuss:
🛠️ 6 sub-tasks needed for SWE
🤖 9 challenges of today's AI in SWE
🔮 9 future directions to address the challenges
w/ collaborators from MIT, Berkeley, Cornell, Stanford, and UPenn
⬇️ (1/n)
Enhancing Code LLM Training with Programmer Attention
Introduces an eye-tracking path augmentation method to expand programmer attention datasets, a pattern abstraction step that refines raw fixations into learnable attention motifs, and a reward-guided strategy for integrating…
Excited to serve as the Web Chair of HumanAISE@FSE'25
Paper Deadline: Feb 25, 2025
Website: humanai4se.github.io
Join us in shaping the future of Human-Centered AI4SE!
Excited to serve as the Web Chair of HumanAISE@FSE'25
Paper Deadline: Feb 25, 2025
Website: humanai4se.github.io
Join us in shaping the future of Human-Centered AI4SE!
Feel free to join our research presentation at 2pm and poster session at 3:30pm🐶 (p.s. the poster has been displayed, but will stay unattended until 3:30pm lol)
Feel free to join our research presentation at 2pm and poster session at 3:30pm🐶 (p.s. the poster has been displayed, but will stay unattended until 3:30pm lol)
Excited to announce our new paper in IEEE Trans. in Med. Imaging, "SWSSL: Sliding window-based self-supervised learning for anomaly detection in high-resolution images", led by Haoyu Dong!
ieeexplore.ieee.org/abstract/docum…
Code: github.com/mazurowski-lab… (1/N)
First on our agenda, ASTRO: An AST-Assisted Approach for Generalizable Neural Clone Detection. A nice collaboration with academia and industry to enable learning AST structures for better clone detection. @InteNSEWorkshop@ICSEconf
Excited to share with everyone an accessible, intuitive tutorial on diffusion models! If you're curious about the math behind diffusion models and how their different interpretations can be unified, please check it out!
Stay tuned for a blog post soon!
arxiv.org/abs/2208.11970
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