Torr, Philip H. S.

Joint Training of Generic CNN-CRF Models with Stochastic Optimization

Kirillov, A., Schlesinger, D., Zheng, S., Savchynskyy, B., Torr, P. H. S., & Rother, C. (2015) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 6

A Scalable Communication Protocol for Networks of Large Language Models

Marro, S., La Malfa, E., Wright, J., Li, G., Shadbolt, N., Wooldridge, M., & Torr, P. (2024) · arXiv

Multi-Agent Systems and NegotiationArtificial Intelligence Applications

Cited by 2

Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap

Channing, G., Sock, J., Clark, R., Torr, P., & de Witt, C. S. (2024) · arXiv

Digital Media Forensic DetectionSpeech Recognition and Synthesis

Cited by 1

Detecting Multi-Agent Collusion Through Multi-Agent Interpretability

Rose, A., Cullen, C., Abdelnabi, S., Torr, P., Kaplowitz, B. G., & de Witt, C. S. (2026) · arXiv

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine Learning

Cited by 0

SETA: Scaling Environments for Terminal Agents

Shen, Q., Huang, Z., Kamanuru, V., Aliev, A., Rainton, J., Awelkair, A., Zeng, Z., Li, J., Dong, S., Yuan, Y., et al. (2026) · arXiv

Reinforcement Learning in RoboticsNatural Language Processing Techniques

Cited by 0