2 citations · 2 across the 8 of their papers we have counts for
17 papers
PocketTSLM: Deploying an On-Device Soft-Prompt Time-Series Language Model for Privacy-Preserving Smartphone Reasoning
Max Rosenblattl, Nikhil Krishnaswamy, Leon Nissen +9
Consumer phones and wearables increasingly collect physiological time-series data, yet most mobile systems treat these streams as summaries or text rather than as temporal evidence…
TimeCap: A Scalable Open-Source Pipeline for Captioning Wearable Health Time-Series Data
Max Rosenblattl, Milana Gurbanova, Karl Aurel Deck +16
Time-series data generated continuously across industrial, environmental, and especially health domains produce multimodal signals whose scale and heterogeneity make their processi…
Unfair and Unsafe: Everyday Bias Triggers Emergent Misalignment
Alex Martí Guiu, Nicolas Zumarraga, Kevin O'Sullivan +2
Emergent misalignment (EM) occurs when fine-tuning a language model to a narrow task makes it misaligned on unrelated ones. Because organizations now routinely fine-tune models on…
Lapras: Latent Reasoning for Time Series Language Models
Yuliang Chen, Yu Yvonne Wu, Patrick Langer +11
Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural language answers and explanatio…
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…
Event History Over Scale: Compact Transformers for Low-Latency Limit Order Book Forecasting
David Schaurecker, Lasse B. Strand, Kevin O'Sullivan +1
Short-horizon price-trend prediction from limit order books in equity and intraday electricity markets requires models that combine predictive quality with low single-sample latenc…
OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning
Tony Chen, Timo Stoffregen, Maxwell Xu +8
Real-world time-series applications increasingly require models that can handle time series forecasting, context-conditioned prediction, and language-based temporal reasoning. Yet…
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…
RestoreBench: Can AI Agents Restore Power Flow Convergence?
Riccardo Mansutti, Andrea Pomarico, Robert Jakob +3
Large Language Model (LLM) agents increasingly automate multi-step engineering workflows through tool use, interpretation of intermediate results, and iterative planning. Diagnosin…
Polistemics: Evaluating LLMs as Information Mediators in Politics & Elections
Baran Peters, Gabor Hollbeck, Robert Jakob +1
As LLMs increasingly shape the political information citizens rely on, no standard exists to assess whether they do so responsibly. We introduce Polistemics, a theory-grounded diag…
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…
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…
Digital Scale: Open-Source On-Device BMI Estimation from Smartphone Camera Images Trained on a Large-Scale Real-World Dataset
Frederik Rajiv Manichand, Robin Deuber, Robert Jakob +4
Estimating Body Mass Index (BMI) from camera images with machine learning models enables rapid weight assessment when traditional methods are unavailable or impractical, such as in…
Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
Sahar Salimpour, Lei Fu, Kajetan Rachwał +8
Foundation models, including large language models (LLMs) and vision-language models (VLMs), have recently enabled novel approaches to robot autonomy and human-robot interfaces. In…