Merlion: A Machine Learning Library for Time Series. - Aadyot Bhatnagar; Paul Kassianik; Chenghao Liu; Tian Lan 006; Wenzhuo Yang; Rowan Cassius; Doyen Sahoo; Devansh Arpit; Sri Subramanian; Gerald Woo; Amrita Saha; Arun Kumar Jagota; et al. (CoRR, 2021)

BigIssue: A Realistic Bug Localization Benchmark. - Paul Kassianik; Erik Nijkamp; Bo Pang 004; Yingbo Zhou; Caiming Xiong (CoRR, 2022)

Merlion: End-to-End Machine Learning for Time Series. - Aadyot Bhatnagar; Paul Kassianik; Chenghao Liu; Tian Lan 006; Wenzhuo Yang; Rowan Cassius; Doyen Sahoo; Devansh Arpit; Sri Subramanian; Gerald Woo; Amrita Saha; Arun Kumar Jagota; et al. (J. Mach. Learn. Res., 2023)

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. - Anay Mehrotra; Manolis Zampetakis; Paul Kassianik; Blaine Nelson; Hyrum S. Anderson; Yaron Singer; Amin Karbasi (NeurIPS, 2024)

Extracting Memorized Training Data via Decomposition. - Ellen Su; Anu Vellore; Amy Chang; Raffaele Mura; Blaine Nelson; Paul Kassianik; Amin Karbasi (CoRR, 2024)

Adversarial Reasoning at Jailbreaking Time. - Mahdi Sabbaghi; Paul Kassianik; George J. Pappas; Yaron Singer; Amin Karbasi; Hamed Hassani (CoRR, 2025)

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report. - Paul Kassianik; Baturay Saglam; Alexander Chen; Blaine Nelson; Anu Vellore; Massimo Aufiero; Fraser Burch; Dhruv Kedia; Avi Zohary; Sajana Weerawardhena; Aman Priyanshu; Adam Swanda; et al. (CoRR, 2025)

Capability-Based Scaling Laws for LLM Red-Teaming. - Alexander Panfilov; Paul Kassianik; Maksym Andriushchenko; Jonas Geiping (CoRR, 2025)

Large Language Models Encode Semantics in Low-Dimensional Linear Subspaces. - Baturay Saglam; Paul Kassianik; Blaine Nelson; Sajana Weerawardhena; Yaron Singer; Amin Karbasi (CoRR, 2025)