4 papers · 1 filter
Twice Upon a Time: Complementary Representations for Time-Series Reasoning
Hedi Zisling, Liran Nochumsohn, Ilan Naiman +2
Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what information should their time-ser…
XCTFormer: Leveraging Cross-Channel and Cross-Time Dependencies for Enhanced Time-Series Analysis
Israel Zexer, Omri Azencot
Multivariate time-series analysis involves extracting informative representations from sequences of multiple interdependent variables, supporting tasks such as forecasting, imputat…
Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exits
Yizhak Yisrael Elboher, Avraham Raviv, Amihay Elboher +4
Ensuring the safety and efficiency of AI systems is a central goal of modern research. Formal verification provides guarantees of neural network robustness, while early exits impro…
Disentanglement Beyond Static vs. Dynamic: A Benchmark and Evaluation Framework for Multi-Factor Sequential Representations
Tal Barami, Nimrod Berman, Ilan Naiman +3
Learning disentangled representations in sequential data is a key goal in deep learning, with broad applications in vision, audio, and time series. While real-world data involves m…