REPOGEO REPORT · LITE

Tebmer/Awesome-Knowledge-Distillation-of-LLMs

Default branch main · commit c96c71a9 · scanned 5/16/2026, 1:53:29 PM

GitHub: 1,280 stars · 72 forks

AI VISIBILITY SCORE

22 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

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 Tebmer/Awesome-Knowledge-Distillation-of-LLMs, 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.

OVERALL DIRECTION

hightopics#1

Add 'awesome-list' and 'paper-collection' topics

Why:

CURRENT

alignment, compression, data-augmentation, data-synthesis, feedback, instruction-following, kd, knowledge-distillation, large-language-model, llm, multi-modal, self-distillation, self-training, supervised-finetuning, survey

COPY-PASTE FIX

awesome-list, paper-collection, alignment, compression, data-augmentation, data-synthesis, feedback, instruction-following, kd, knowledge-distillation, large-language-model, llm, multi-modal, self-distillation, self-training, supervised-finetuning, survey

highlicense#2

Add a LICENSE file to the repository

Why:

CURRENT

(no LICENSE file detected — the repo has no recognizable license)

COPY-PASTE FIX

Create a `LICENSE` file in the repository root containing the text of an appropriate open-source license (e.g., MIT, Apache-2.0, or GPL-3.0) to clarify usage terms.

mediumhomepage#3

Set the repository homepage URL

Why:

COPY-PASTE FIX

Set the GitHub repository's homepage URL to `https://arxiv.org/abs/2402.13116` (the associated survey 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.

Recall

0 / 2

0% of queries surface Tebmer/Awesome-Knowledge-Distillation-of-LLMs

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Hugging Face Transformers

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Hugging Face Transformers · recommended 1×
ð§ Accelerate · recommended 1×
Optimum · recommended 1×
PyTorch Lightning · recommended 1×
DeepSpeed · recommended 1×

CATEGORY QUERY
How to distill knowledge from large language models to create smaller, efficient versions?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers
2. ð§ Accelerate
3. Optimum
4. PyTorch Lightning
5. DeepSpeed
6. DistilBERT
7. TensorFlow Lite
8. ONNX Runtime
9. OpenVINO
AI recommended 9 alternatives but never named Tebmer/Awesome-Knowledge-Distillation-of-LLMs. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What strategies can I use to improve smaller models with knowledge from LLMs?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers (huggingface/transformers)
2. PyTorch (pytorch/pytorch)
3. TensorFlow (tensorflow/tensorflow)
4. OpenVINO (openvinotoolkit/openvino)
5. OpenAI API
6. Anthropic Claude
7. LangChain (langchain-ai/langchain)
8. LlamaIndex (run-llama/llama_index)
9. PyTorch Lightning (Lightning-AI/lightning)
10. Scikit-learn (scikit-learn/scikit-learn)
11. Cohere Embed
AI recommended 11 alternatives but never named Tebmer/Awesome-Knowledge-Distillation-of-LLMs. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

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 Tebmer/Awesome-Knowledge-Distillation-of-LLMs?
pass
AI did not name Tebmer/Awesome-Knowledge-Distillation-of-LLMs — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts Tebmer/Awesome-Knowledge-Distillation-of-LLMs in production, what risks or prerequisites should they evaluate first?
pass
AI named Tebmer/Awesome-Knowledge-Distillation-of-LLMs 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 Tebmer/Awesome-Knowledge-Distillation-of-LLMs solve, and who is the primary audience?
pass
AI did not name Tebmer/Awesome-Knowledge-Distillation-of-LLMs — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite