Time Series Language Modeling

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16 papers5 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

TEMPO: Time Series Understanding via Discrete Tokenization
Nov 3, 2026Riccardo MaggioniTime Series Tokenization Time Series Language Modeling
Forgis
Perceive, Solve, Reason: Progressive Capability Formation in Time Series-LLMs
Oct 16, 2026Xin Qiu, Junlong Tong, Wei Zhang +1Time Series Reasoning Time Series Language Modeling
EIT-NLP Lab, Eastern Institute of Technology, Ningbo · Zhejiang University · Shanghai Jiao Tong University
Twice Upon a Time: Complementary Representations for Time-Series Reasoning
Oct 15, 2026Hedi Zisling, Liran Nochumsohn, Ilan Naiman +2Time Series Language Modeling Time Series Reasoning
Ben-Gurion University · Google
PocketTSLM: Deploying an On-Device Soft-Prompt Time-Series Language Model for Privacy-Preserving Smartphone Reasoning
Oct 15, 2026Max Rosenblattl, Nikhil Krishnaswamy, Leon Nissen +9Time Series Language Modeling On-Device Language Model Inference
Stanford University, USA · CHI, Technical University of Munich University Hospital, Germany · ETH Zurich, Switzerland +3
TimeCap: A Scalable Open-Source Pipeline for Captioning Wearable Health Time-Series Data
Oct 15, 2026Max Rosenblattl, Milana Gurbanova, Karl Aurel Deck +16Time Series Language Modeling Wearable Health Monitoring
Stanford University, USA · Aionic Labs, Switzerland · Agentic Systems Lab, ETH Zurich, Switzerland +7
Lapras: Latent Reasoning for Time Series Language Models
Oct 8, 2026Yuliang Chen, Yu Yvonne Wu, Patrick Langer +11Time Series Language Modeling Temporal Reasoning in Language Models
Dartmouth College · Aionic Labs · Agentic Systems Lab, ETH Zurich +2
Lotus: Learning to Understand Time-series by Learning to Forecast
Oct 1, 2026Van Dai Do, Huu Hiep Nguyen, Minh Hoang Nguyen +2Time Series Language Modeling Time Series Representation Learning
Deakin’s Applied Artificial Intelligence Initiative, Australia
OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning
Sep 30, 2026Tony Chen, Timo Stoffregen, Maxwell Xu +8Temporal Reasoning in Language Models LLM-Based Time Series Forecasting
Columbia University, USA · Stanford University, USA · Aionic Labs, Switzerland +4
TimeBraid: Unifying Time Series and Language for Understanding and Forecasting
Sep 24, 2026Xinyue Wang, Jiacheng Pang, Kun Zhou +7Unified Multimodal Models Multimodal Pretraining
University of California San Diego · Aether AI · University of Southern California
WaveTLM: Reliable Time-Series Language Modeling through Task Compilation
Sep 16, 2026Jiahui Chen, Bingke Zhu, Hongyu Pan +1LLM Reliability Time-Series Foundation Models
Institute of Automation, Chinese Academy of Sciences Beijing, China
Decoupling Perception from Description: Computation-Grounded Representation Alignment between Multivariate Time Series and Language
Aug 5, 2026Xinran Feng, Yi Xie, Chao Zhang +4Cross-Modal Representation Learning Multimodal Pretraining
Thrust of Financial Technology, The Hong Kong University of Science and Technology (Guangzhou) · Technical University of Munich · Heilbronn Data Science Center, Munich Data Science Institute +1
TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series
Aug 4, 2026Nicolas Zumarraga, Lorenzo Steno, Ning Wang +9Language Modeling Anomaly Localization
1Agentic Systems Lab, ETH Zürich · 3Seldon Technologies · 2Stanford University +4
Beyond Uniform Tokens: Adaptive Compression for Time Series Language Models
Jun 11, 2026Jialin Gan, Xin Qiu, Guangzhe Chen +1LLM Inference Acceleration Multimodal Token Compression
Zhejiang University · Harbin Institute of Technology · Shandong University
Time Series as Language: A Universal Tokenizer for General-Purpose Time Series Foundation Models
May 31, 2026Yunhao Zhang, Ruiying Qi, Jiale Zheng +3Time Series Tokenization Time Series Generation
Shanghai Jiao Tong University · Huawei Noah’s Ark Lab
LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring
Apr 7, 2026Xiao Qin, Xingyi Song, Tong Liu +4Time Series Language Modeling Predictive Maintenance
Department of Computer Science, University of Warwick, Coventry, UK · Department of Computer Science, University of Sheffield, Sheffield, UK · Advanced Manufacturing Research Centre, University of Sheffield, Sheffield, UK +2
TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoning
Feb 15, 2026Nicolas Zumarraga, Thomas Kaar, Ning Wang +12Contextual Anomaly Detection Time Series Reasoning
1Agentic Systems Lab, ETH Zurich · 2Stanford University · 3Traffic Engineering Group, Institute for Transport Planning and Systems, ETH Zurich +4

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TEMPO: Time Series Understanding via Discrete Tokenization

Riccardo Maggioni

Forgis

Time Series Tokenization Time Series Language Modeling Time Series Classification

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Time-series interpretation often requires both numerical observations and textual context. Integrating these inputs into a pretrained language model raises a representation question: how should a signal enter the model's token sequence? We present TEMPO, which extends an LLM's vocabulary with discrete codes from a context-aware Transformer tokenizer using finite scalar quantization. A frozen tokenizer maps four-step patches to a 625-code vocabulary; signal tokens, scale statistics, and text are then processed by the LLM's existing self-attention layers. Adaptation updates the new token embeddings and DoRA adapters. With a Qwen3-4B backbone and task-specific fine-tuning, TEMPO achieves macro-F1 scores of 89.0% on activity recognition, 85.0% on sleep staging, and 86.0% on bearing-fault diagnosis. Time-series question answering and qualitative bearing-diagnosis examples further illustrate how this interface combines signal representations with textual context. Together, these results demonstrate the utility of discrete vocabulary extension for time-series understanding.