RRepoGEO

REPOGEO REPORT · LITE

SinclairCoder/Instruction-Tuning-Papers

Default branch main · commit 177274f7 · scanned 6/16/2026, 7:02:23 AM

GitHub: 769 stars · 23 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 SinclairCoder/Instruction-Tuning-Papers, 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
  • highreadme#1
    Reposition README opening to clarify it's a paper list

    Why:

    CURRENT
    # Instruction-Tuning-Papers    A trend starts from `Natrural-Instruction` (ACL 2022), `FLAN` (ICLR 2022) and `T0` (ICLR 2022). What's the instruction-tuning? It aims to teach language models to follow natural language (including prompt, positive or negative examples, and constraints etc.), to perform better multi-task learning on training tasks and generalization on unseen tasks.
    COPY-PASTE FIX
    # Instruction-Tuning-Papers: A Curated Reading List of Key Papers on Instruction Tuning This repository is a curated reading list of essential research papers on instruction tuning, a pivotal trend in large language model development. It tracks the evolution of instruction tuning from foundational works like Natural-Instruction (ACL 2022), FLAN (ICLR 2022), and T0 (ICLR 2022). Instruction tuning aims to teach language models to follow natural language instructions (including prompts, examples, and constraints) for better multi-task learning and generalization on unseen tasks.
  • highlicense#2
    Add a LICENSE file

    Why:

    COPY-PASTE FIX
    Choose and add a standard open-source LICENSE file (e.g., MIT, Apache-2.0) to the repository root.
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    Add a relevant URL (e.g., a project page, a related blog post, or even the repository URL itself if no external page exists) to the 'Homepage' field in the repository settings.

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 SinclairCoder/Instruction-Tuning-Papers
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. PromptPerfect · recommended 1×
  3. OpenAI GPT-3/GPT-4 · recommended 1×
  4. Anthropic Claude · recommended 1×
  5. Google PaLM 2 / Gemini · recommended 1×
  • CATEGORY QUERY
    How can I improve large language model performance on unseen tasks using instruction-based methods?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. PromptPerfect
    3. OpenAI GPT-3/GPT-4
    4. Anthropic Claude
    5. Google PaLM 2 / Gemini
    6. Alpaca
    7. Vicuna
    8. FLAN
    9. LlamaIndex

    AI recommended 9 alternatives but never named SinclairCoder/Instruction-Tuning-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective strategies for achieving cross-task generalization in natural language processing?
    you: not recommended
    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 SinclairCoder/Instruction-Tuning-Papers?
    pass
    AI did not name SinclairCoder/Instruction-Tuning-Papers — 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 SinclairCoder/Instruction-Tuning-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SinclairCoder/Instruction-Tuning-Papers 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 SinclairCoder/Instruction-Tuning-Papers solve, and who is the primary audience?
    pass
    AI did not name SinclairCoder/Instruction-Tuning-Papers — 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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SinclairCoder/Instruction-Tuning-Papers — 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
SinclairCoder/Instruction-Tuning-Papers — RepoGEO report