RRepoGEO

REPOGEO REPORT · LITE

voidism/DoLa

Default branch main · commit 805230e5 · scanned 6/14/2026, 5:32:45 AM

GitHub: 554 stars · 69 forks

AI VISIBILITY SCORE
35 /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
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 voidism/DoLa, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening to clarify DoLa's core method and category.

    Why:

    CURRENT
    DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

Code for the ICLR 2024 paper "DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models"
    COPY-PASTE FIX
    DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

DoLa is a novel *decoding strategy* for Large Language Models (LLMs) that significantly improves factuality and reduces hallucinations *without* requiring external knowledge retrieval (RAG), fine-tuning, or preference optimization (DPO). This repository provides the official implementation for our ICLR 2024 paper.
  • highlicense#2
    Add a LICENSE file to the repository.

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root. Given the MIT badge in the README, consider using the standard MIT License text.

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 voidism/DoLa
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. LlamaIndex · recommended 1×
  3. Azure AI Search · recommended 1×
  4. Pinecone · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How to reduce factual errors and hallucinations when generating text with large language models?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Azure AI Search
    4. Pinecone
    5. Weaviate
    6. Qdrant
    7. OpenAI API
    8. Hugging Face Transformers
    9. Google Cloud Vertex AI
    10. BERT
    11. RoBERTa
    12. Scale AI
    13. Appen
    14. Neo4j
    15. Wikidata
    16. GPT-4
    17. Claude 3 Opus
    18. Google Gemini
    19. TruthfulQA

    AI recommended 19 alternatives but never named voidism/DoLa. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What decoding strategies improve large language model factuality without fine-tuning or external knowledge?
    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 voidism/DoLa?
    pass
    AI named voidism/DoLa explicitly

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

  • If a team adopts voidism/DoLa in production, what risks or prerequisites should they evaluate first?
    pass
    AI named voidism/DoLa 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 voidism/DoLa solve, and who is the primary audience?
    pass
    AI named voidism/DoLa 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 voidism/DoLa. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/voidism/DoLa.svg)](https://repogeo.com/en/r/voidism/DoLa)
HTML
<a href="https://repogeo.com/en/r/voidism/DoLa"><img src="https://repogeo.com/badge/voidism/DoLa.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

voidism/DoLa — 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