5 papers
C3PO: Optimized Large Language Model Cascades with Probabilistic Cost Constraints for Reasoning
Antonios Valkanas, Soumyasundar Pal, Pavel Rumiantsev +2
Large language models (LLMs) have achieved impressive results on complex reasoning tasks, but their high inference cost remains a major barrier to real-world deployment. A promisin…
Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
Mohammad Ali Alomrani, Yingxue Zhang, Derek Li +14
Large language models (LLMs) have rapidly progressed into general-purpose agents capable of solving a broad spectrum of tasks. However, current models remain inefficient at reasoni…
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
Yitian Zhang, Liheng Ma, Antonios Valkanas +2
Koopman operator theory provides a framework for nonlinear dynamical system analysis and time-series forecasting by mapping dynamics to a space of real-valued measurement functions…
MODL: Multilearner Online Deep Learning
Antonios Valkanas, Boris N. Oreshkin, Mark Coates
Online deep learning tackles the challenge of learning from data streams by balancing two competing goals: fast learning and deep learning. However, existing research primarily emp…
Personalized Negative Reservoir for Incremental Learning in Recommender Systems
Antonios Valkanas, Yuening Wang, Yingxue Zhang +1
Recommender systems have become an integral part of online platforms. Every day the volume of training data is expanding and the number of user interactions is constantly increasin…