Phillip Wallis

According to our database, Phillip Wallis authored at least 12 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Reinforcement Learning with Backtracking Feedback.

Bilgehan Sel, Vaishakh Keshava, Phillip Wallis, Lukas Rutishauser, Ming Jin, Dingcheng Li

CoRR, February, 2026

CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution.

Minbeom Kim, Mihir Parmar, Phillip Wallis, Lesly Miculicich, Kyomin Jung, Krishnamurthy Dj Dvijotham, Long T. Le, Tomas Pfister

CoRR, February, 2026

2025

Adversarial Reinforcement Learning for Large Language Model Agent Safety.

Zizhao Wang, Dingcheng Li, Vaishakh Keshava, Phillip Wallis, Ananth Balashankar, Peter Stone, Lukas Rutishauser

CoRR, October, 2025

Backtracking for Safety.

Bilgehan Sel, Dingcheng Li, Phillip Wallis, Vaishakh Keshava, Ming Jin, Siddhartha Reddy Jonnalagadda

CoRR, March, 2025

AnoLLM: Large Language Models for Tabular Anomaly Detection.

Che-Ping Tsai, Ganyu Teng, Phillip Wallis, Wei Ding

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2022

LoRA: Low-Rank Adaptation of Large Language Models.

Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen

Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient Fine-Tuning of Deep Neural Networks with Effective Parameter Allocation.

Phillip Wallis, Xubo Song

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

LoRA: Low-Rank Adaptation of Large Language Models.

Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Weizhu Chen

CoRR, 2021

2020

Automatic Event Detection of REM Sleep Without Atonia From Polysomnography Signals Using Deep Neural Networks.

Phillip Wallis, Daniel Yaeger, Alexander Kain, Xubo Song, Miranda Lim

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Differential Equation Units: Learning Functional Forms of Activation Functions from Data.

MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions.

MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas

CoRR, 2019

Learning Semantic Relationships from Medical Codes.

Phillip Wallis, Padideh Danaee

Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019