Awesome-TimeSeries-SpatioTemporal-LM-LLM

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Awesome-TimeSeries-SpatioTemporal-LM-LLM is a curated list of large language models (LLMs) and foundation models for temporal data. It provides resources including papers, code, and applications for time series, spatio-temporal, and event data.

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free

Free tier

Yes

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Skill level

Technical

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What is Awesome-TimeSeries-SpatioTemporal-LM-LLM?

Awesome-TimeSeries-SpatioTemporal-LM-LLM offers a comprehensive, curated collection of resources focused on large language models (LLMs) and foundation models specifically designed for temporal data. This includes a wide array of materials pertinent to time series, spatio-temporal, and event data. The list is a valuable hub for researchers and developers, providing access to relevant papers, code implementations, and practical applications of these advanced models in various domains.

Best used for

Discovering and researching large language models and foundation models specifically designed for various types of temporal data.

Common actions

Find LLM resources

Research temporal data models

Explore spatio-temporal LLMs

Discover code for time series

Learn about foundation models

collaborationautomated workflowlow-code/no-codeworkflowsdeepfake"AI Agents"face swappingopen-sourcegithub copilot

Capabilities

Key features

Curated list
LLMs for temporal data
Time series resources
Spatio-temporal models
Event data applications

Target Audience

ResearchersData ScientistsMachine Learning EngineersAcademics

Integrations

Not yet documented

Pricing & Plans

free

Free

FAQs

Does this resource list include proprietary or paid LLMs, or is it focused solely on open-source models for temporal data?

As a curated list, Awesome-TimeSeries-SpatioTemporal-LM-LLM aims to be comprehensive, including references to both open-source and proprietary models where relevant to the application of LLMs for temporal and spatio-temporal data. The focus is on the research and application rather than licensing.

How frequently is the Awesome-TimeSeries-SpatioTemporal-LM-LLM list updated with new papers, code, and resources?

The frequency of updates depends on the maintainers and the rapid pace of research in this field. Users can typically check the repository's commit history or contribution guidelines for an indication of how actively it is maintained and updated with the latest advancements.

Are there specific criteria for resources to be included in this curated list, such as a minimum citation count or publication venue?

The inclusion criteria for Awesome-TimeSeries-SpatioTemporal-LM-LLM generally prioritize relevance to LLMs/foundation models for temporal, spatio-temporal, and event data. While quality is implied, specific metrics like citation counts are not typically strict requirements for inclusion in such curated lists, aiming for broad coverage of impactful work.

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Coding & Development › Open Source & Models

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