6 papers
Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents
Lasse B. Strand, Robert Jakob, Kevin O'Sullivan +1
Retrieval-augmented generation (RAG) is a widely used approach for grounding large language models (LLMs) in external knowledge. However, configuring a pipeline is an expensive hyp…
TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models
Martin Maritsch, Timo Stoffregen, Thomas Kaar +36
Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…
ConRAG: Lightweight inference of multi-hop relations
Kilian Bänziger, Sonia Laguna, Markus Kreft +4
Understanding how two entities are connected often requires tracing multi-hop relations across documents to identify intermediate entities and supporting evidence that explain a co…
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…
Patient-Level Multimodal Question Answering from Multi-Site Auscultation Recordings
Fan Wu, Tsai-Ning Wang, Nicolas Zumarraga +8
Auscultation is a vital diagnostic tool, yet its utility is often limited by subjective interpretation. While general-purpose Audio-Language Models (ALMs) excel in general domains,…
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…