RRepoGEO

REPOGEO REPORT · LITE

Qihoo360/Light-R1

Default branch main · commit 40b5965e · scanned 6/6/2026, 9:42:35 AM

GitHub: 767 stars · 47 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 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 Qihoo360/Light-R1, 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
  • highabout#1
    Add a concise "About" description

    Why:

    COPY-PASTE FIX
    Light-R1 provides state-of-the-art large language models (LLMs) and training methodologies, including Curriculum SFT, DPO, and RL, specifically optimized for advanced mathematical problem-solving and complex Chain-of-Thought (COT) reasoning.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm, large-language-models, fine-tuning, reinforcement-learning, sft, dpo, math-reasoning, chain-of-thought, deep-learning, artificial-intelligence
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://huggingface.co/collections/qihoo360/light-r1-67c675125e2443d7d5ed133d

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 Qihoo360/Light-R1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4 · recommended 2×
  2. GPT-3.5 · recommended 1×
  3. Llama 2 · recommended 1×
  4. Mistral · recommended 1×
  5. MATH · recommended 1×
  • CATEGORY QUERY
    How can I enhance large language models for advanced mathematical problem-solving and reasoning?
    you: not recommended
    AI recommended (in order):
    1. GPT-3.5
    2. Llama 2
    3. Mistral
    4. MATH
    5. GSM8K
    6. MiniF2F
    7. AQUA-RAT
    8. GPT-4
    9. Claude 3
    10. Gemini Advanced
    11. OpenAI's Code Interpreter
    12. Google Colab
    13. Wolfram Alpha API
    14. SymPy (sympy/sympy)
    15. SageMath (sagemath/sage)
    16. Pinecone
    17. Weaviate (weaviate/weaviate)
    18. ChromaDB (chroma-core/chroma)
    19. LaTeX
    20. MathML
    21. Wikipedia
    22. MathWorld
    23. Lean (leanprover/lean4)
    24. Mathlib (leanprover-community/mathlib4)
    25. Coq (coq/coq)

    AI recommended 25 alternatives but never named Qihoo360/Light-R1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective methods for fine-tuning LLMs to achieve state-of-the-art performance on complex tasks?
    you: not recommended
    AI recommended (in order):
    1. peft (huggingface/peft)
    2. transformers (huggingface/transformers)
    3. bitsandbytes (TimDettmers/bitsandbytes)
    4. Argilla (argilla-io/argilla)
    5. GPT-4
    6. Claude 3 Opus
    7. trl (huggingface/trl)
    8. OpenAI's API
    9. Anthropic's API
    10. FlashAttention (Dao-AILab/flash-attention)
    11. DeepSpeed (microsoft/DeepSpeed)
    12. FSDP (pytorch/pytorch)
    13. Mixtral 8x7B
    14. nlaug

    AI recommended 14 alternatives but never named Qihoo360/Light-R1. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Qihoo360/Light-R1?
    pass
    AI named Qihoo360/Light-R1 explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Qihoo360/Light-R1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Qihoo360/Light-R1 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 Qihoo360/Light-R1 solve, and who is the primary audience?
    pass
    AI named Qihoo360/Light-R1 explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Qihoo360/Light-R1 — 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