3 papers
cs.LG2026
TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series
Nicolas Zumarraga, Lorenzo Steno, Ning Wang +9
Precise anomaly localization over long-context time series is a crucial task in monitoring applications across clinical care, industrial operations, financial services, and logisti…
cs.LG2026
TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoning
Nicolas Zumarraga, Thomas Kaar, Ning Wang +12
Time Series Language Models (TSLMs) promise reasoning over real-world temporal data, but their ability to retrieve and reason over long time-series remains largely untested. We int…
cs.LG2026
OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
Patrick Langer, Thomas Kaar, Max Rosenblattl +19
LLMs have emerged as powerful tools for interpreting multimodal data. In medicine, they hold particular promise for synthesizing large volumes of clinical information into actionab…