Cover Image

Chronicle: A Multimodal Foundation Model for Joint Language and Time Series Understanding

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Quinlan, Paul, Levasseur, Jeremy, Li, Qingguo, Zhu, Xiaodan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Chat-TS: Enhancing Multi-Modal Reasoning Over Time-Series and Natural Language Data
by: Quinlan, Paul, et al.
Published: (2025)

ADAPTive Input Training for Many-to-One Pre-Training on Time-Series Classification
by: Quinlan, Paul, et al.
Published: (2026)

MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning
by: Ye, Jiexia, et al.
Published: (2024)

SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models
by: Rizvi, Md Imbesat Hassan, et al.
Published: (2024)

TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models
by: Wang, Jiahao, et al.
Published: (2024)

In-Context Fine-Tuning for Time-Series Foundation Models
by: Das, Abhimanyu, et al.
Published: (2024)

MIO: A Foundation Model on Multimodal Tokens
by: Wang, Zekun, et al.
Published: (2024)

Foundations of Large Language Models
by: Xiao, Tong, et al.
Published: (2025)

Fine-Tuning a Time Series Foundation Model with Wasserstein Loss
by: Chernov, Andrei
Published: (2024)

Large Language Models for Time Series: A Survey
by: Zhang, Xiyuan, et al.
Published: (2024)

Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Series
by: Chang, Ching, et al.
Published: (2025)

Dissecting Chronos: Sparse Autoencoders Reveal Causal Feature Hierarchies in Time Series Foundation Models
by: Mishra, Anurag
Published: (2026)

STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions
by: Fan, Junjie, et al.
Published: (2025)

Thoth: Mid-Training Bridges LLMs to Time Series Understanding
by: Lin, Jiafeng, et al.
Published: (2026)

When Does Multimodality Lead to Better Time Series Forecasting?
by: Zhang, Xiyuan, et al.
Published: (2025)

Agent-Omni: Test-Time Multimodal Reasoning via Model Coordination for Understanding Anything
by: Lin, Huawei, et al.
Published: (2025)

Reconstructing Sepsis Trajectories from Clinical Case Reports using LLMs: the Textual Time Series Corpus for Sepsis
by: Noroozizadeh, Shahriar, et al.
Published: (2025)

Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models
by: Kurisinkel, Litton Jose, et al.
Published: (2024)

SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling
by: Rizvi, Md Imbesat Hassan, et al.
Published: (2025)

Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation
by: Li, Xianzhi, et al.
Published: (2024)

PMOA-TTS: Introducing the PubMed Open Access Textual Times Series Corpus
by: Noroozizadeh, Shahriar, et al.
Published: (2025)

UniCL: A Universal Contrastive Learning Framework for Large Time Series Models
by: Li, Jiawei, et al.
Published: (2024)

The Chronicles of RAG: The Retriever, the Chunk and the Generator
by: Finardi, Paulo, et al.
Published: (2024)

Apple Intelligence Foundation Language Models
by: Gunter, Tom, et al.
Published: (2024)

nach0: Multimodal Natural and Chemical Languages Foundation Model
by: Livne, Micha, et al.
Published: (2023)

Many-Shot In-Context Learning in Multimodal Foundation Models
by: Jiang, Yixing, et al.
Published: (2024)

Variational Language Concepts for Interpreting Foundation Language Models
by: Wang, Hengyi, et al.
Published: (2024)

Toward Understanding BERT-Like Pre-Training for DNA Foundation Models
by: Liang, Chaoqi, et al.
Published: (2023)

Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting
by: Riachi, Roland, et al.
Published: (2025)

Understanding Understanding: A Pragmatic Framework Motivated by Large Language Models
by: Leyton-Brown, Kevin, et al.
Published: (2024)

Can Large Language Models Understand Intermediate Representations in Compilers?
by: Jiang, Hailong, et al.
Published: (2025)

Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models
by: Jiang, Jiachen, et al.
Published: (2025)

TracrBench: Generating Interpretability Testbeds with Large Language Models
by: Thurnherr, Hannes, et al.
Published: (2024)

Towards Reasoning-Preserving Unlearning in Multimodal Large Language Models
by: Li, Hongji, et al.
Published: (2025)

VLSU: Mapping the Limits of Joint Multimodal Understanding for AI Safety
by: Palaskar, Shruti, et al.
Published: (2025)

HEMM: Holistic Evaluation of Multimodal Foundation Models
by: Liang, Paul Pu, et al.
Published: (2024)

Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
by: Liu, Fuqiang, et al.
Published: (2024)

Emergent Semantic Role Understanding in Language Models
by: Griffiths, Carla, et al.
Published: (2026)

Understanding Subword Compositionality of Large Language Models
by: Peng, Qiwei, et al.
Published: (2025)

Understanding and Mitigating Tokenization Bias in Language Models
by: Phan, Buu, et al.
Published: (2024)