REPOGEO REPORT · LITE
ngruver/llmtime
Default branch main · commit f74234c4 · scanned 6/3/2026, 3:23:13 AM
GitHub: 827 stars · 178 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ngruver/llmtime, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highabout#1Add a concise 'About' description
Why:
COPY-PASTE FIXLLMTime is a method for zero-shot time series forecasting using large language models (LLMs) by encoding numbers as text and sampling extrapolations as text completions.
- hightopics#2Add relevant topics to improve categorization
Why:
COPY-PASTE FIX["llm", "large-language-models", "time-series", "forecasting", "zero-shot", "machine-learning", "neurips-2023"]
- mediumreadme#3Add a clear, concise project summary to the README's introduction
Why:
CURRENT# Large Language Models Are Zero Shot Time Series Forecasters This repository contains the code for the paper
COPY-PASTE FIX# Large Language Models Are Zero Shot Time Series Forecasters LLMTime is a novel method for zero-shot time series forecasting that leverages large language models (LLMs) by encoding numerical data as text and generating future predictions through text completions. This approach allows LLMs to outperform many traditional time series methods without any prior training on the target dataset. This repository contains the code for the paper
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Prophet · recommended 1×
- Exponential Smoothing · recommended 1×
- ARIMA/SARIMA · recommended 1×
- Theta method · recommended 1×
- Naive/Seasonal Naive Forecasts · recommended 1×
- CATEGORY QUERYHow to perform time series forecasting without needing to train a specific model?you: not recommendedAI recommended (in order):
- Prophet
- Exponential Smoothing
- ARIMA/SARIMA
- Theta method
- Naive/Seasonal Naive Forecasts
- NeuralProphet
AI recommended 6 alternatives but never named ngruver/llmtime. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat tools enable large language models for time series prediction tasks?you: not recommendedAI recommended (in order):
- Hugging Face Transformers (huggingface/transformers)
- PyTorch (pytorch/pytorch)
- TensorFlow (tensorflow/tensorflow)
- Pandas (pandas-dev/pandas)
- Scikit-learn (scikit-learn/scikit-learn)
- Nixtla (Nixtla/nixtla)
- Weights & Biases (wandb/wandb)
- Optuna (optuna/optuna)
- Ray Tune (ray-project/ray)
AI recommended 9 alternatives but never named ngruver/llmtime. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of ngruver/llmtime?passAI named ngruver/llmtime explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts ngruver/llmtime in production, what risks or prerequisites should they evaluate first?passAI named ngruver/llmtime explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo ngruver/llmtime solve, and who is the primary audience?passAI named ngruver/llmtime explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of ngruver/llmtime. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
[](https://repogeo.com/en/r/ngruver/llmtime)<a href="https://repogeo.com/en/r/ngruver/llmtime"><img src="https://repogeo.com/badge/ngruver/llmtime.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
ngruver/llmtime — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite