What If TSF: Reframing Time Series Forecasting as Scenario-Guided Multimodal Forecasting

arXiv:2601.08509 · cs.AI, cs.CL · Submitted 2026-01-13 · Read on arXiv

cs.AI, cs.CL

Submitted: 2026-01-13

Updated: 2026-09-25

Code: https://github.com/jinkwan1115/WhatIfTSF

Terminology

• Benchmark — 54× in this paper · explained in 2 episodes
• Accuracy — 31× in this paper · explained in 1 episode
• Time Series Forecasting — 20× in this paper · explained in 3 episodes
• Foundation Model — 6× in this paper · explained in 3 episodes
• Verification — 5× in this paper · explained in 2 episodes
• What If TSF — 5× in this paper
• Transformer — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Energy Information Administration — 3× in this paper
• Foundation Models — 3× in this paper · explained in 7 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Abundance — 2× in this paper · explained in 1 episode
• Global Knowledge Graph — 2× in this paper
• Hallucination — 2× in this paper · explained in 3 episodes
• Knowledge Graph — 2× in this paper · explained in 7 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Frustration — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Mean Squared Error — 1× in this paper
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Time Series Foundation Models (TSFMs) — 1× in this paper · explained in 2 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• XForecast: Evaluating Natural Language Explanations for Time Series Forecasting
• Chronos-2: From Univariate to Universal Forecasting
• Beyond Na\"ive Prompting: Strategies for Improved Context-aided Forecasting with LLMs
• Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Series
• Context Matters: Leveraging Contextual Features for Time Series Forecasting
• MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
• Forecasting for monetary policy
• Metadata Matters for Time Series: Informative Forecasting with Transformers
• Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions
• The Llama 3 Herd of Models
• Mistral 7B
• Mixtral of Experts
• TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop
• Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
• Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data
• Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement
• Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
• Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative
• DP-GPT4MTS: Dual-Prompt Large Language Model for Textual-Numerical Time Series Forecasting
• Moirai 2.0: When Less Is More for Time Series Forecasting

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