TimeInteract: Towards Real-Time Interactive Intelligence for Streaming Time Series

arXiv:2609.26389 · cs.LG, cs.AI · Submitted 2026-09-22 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-09-22

Updated: 2026-09-22

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Verification — 23× in this paper · explained in 2 episodes
• Adaptation — 10× in this paper · explained in 1 episode
• Grounding — 7× in this paper · explained in 3 episodes
• Adaptivity — 6× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Distillation — 6× in this paper · explained in 2 episodes
• KV cache — 6× in this paper · explained in 3 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Proactive Temporal Warning — 5× in this paper
• Time Series Forecasting — 5× in this paper · explained in 3 episodes
• F1 Score — 4× in this paper · explained in 3 episodes
• Instant Query Answering — 4× in this paper
• Vision-language models — 4× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• User-Guided Adaptation — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Information Leakage — 2× in this paper · explained in 2 episodes
• Semantic Correctness — 2× in this paper
• Temporal Reasoning — 2× in this paper · explained in 2 episodes
• Time to First Token — 2× in this paper
• Transformer — 2× in this paper · explained in 2 episodes
• Verifier — 2× in this paper · explained in 2 episodes
• Adaptation Success Rate — 1× in this paper
• Analyzer — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Correct Event Hit Rate — 1× in this paper
• Decoupling — 1× in this paper · explained in 2 episodes
• Edge Deployment — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Ontology — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Understanding and Instruction Fulfillment Rate — 1× in this paper

Sources

• Qwen2.5-VL Technical Report
• TimeSeriesExam: A time series understanding exam
• From Turn-Taking to Synchronous Dialogue: A Survey of Full-Duplex Spoken Language Models
• Moshi: a speech-text foundation model for real-time dialogue
• Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• LVCG: Learning ECG Representations in the Latent Vectorcardiogram Space
• TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning
• OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
• GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring
• A Survey of Full-Duplex Spoken Dialogue Systems: Architectural Hierarchy, Interaction Ontology, and Decision State Machine
• TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
• It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
• Think While Watching: Online Streaming Segment-Level Memory for Multi-Turn Video Reasoning in Multimodal Large Language Models
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• Freeze-Omni: A Smart and Low Latency Speech-to-speech Dialogue Model with Frozen LLM
• ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning
• Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming
• Audio Interaction Model

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