REPOGEO REPORT · LITE

quqxui/Awesome-LLM4IE-Papers

Default branch main · commit ee1db165 · scanned 6/21/2026, 7:32:56 PM

GitHub: 1,063 stars · 62 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 quqxui/Awesome-LLM4IE-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

Clarify README's opening sentence to emphasize it's a paper collection/survey

Why:

CURRENT

Awesome papers about generative Information extraction using LLMs

COPY-PASTE FIX

This repository provides an awesome, curated collection of research papers and a comprehensive survey on generative Information Extraction (IE) using Large Language Models (LLMs).

highlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root. If the content is intended to be freely shareable and reusable, consider a permissive license like MIT or Apache-2.0. If the content is derived from other sources, ensure the chosen license is compatible.

mediumabout#3

Refine the repository description for clarity

Why:

CURRENT

Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)

COPY-PASTE FIX

A curated collection of research papers and a comprehensive survey on generative Information Extraction (IE) using Large Language Models (LLMs), ideal for researchers and practitioners.

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 quqxui/Awesome-LLM4IE-Papers

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Anthropic Claude 3

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Anthropic Claude 3 · recommended 2×
OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
Google Gemini · recommended 1×
Mistral Large / Mixtral 8x7B · recommended 1×
Llama 3 · recommended 1×

CATEGORY QUERY
What are the best approaches for generative information extraction using large language models?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-4 / GPT-3.5 Turbo
2. Anthropic Claude 3
3. Google Gemini
4. Mistral Large / Mixtral 8x7B
5. Llama 3
6. Cohere Command R+
7. OpenAI GPT-3.5 Turbo (fine-tuned)
AI recommended 7 alternatives but never named quqxui/Awesome-LLM4IE-Papers. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How can large language models be applied for few-shot or zero-shot information extraction?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-4
2. Anthropic Claude 3
3. Google Gemini Advanced
4. Meta Llama 3
5. Mistral 7B / Mixtral 8x7B
6. Falcon 7B / 40B
7. Google Cloud Document AI
8. Amazon Textract
9. Microsoft Azure AI Document Intelligence
AI recommended 9 alternatives but never named quqxui/Awesome-LLM4IE-Papers. 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 quqxui/Awesome-LLM4IE-Papers?
pass
AI did not name quqxui/Awesome-LLM4IE-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 quqxui/Awesome-LLM4IE-Papers in production, what risks or prerequisites should they evaluate first?
pass
AI named quqxui/Awesome-LLM4IE-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 quqxui/Awesome-LLM4IE-Papers solve, and who is the primary audience?
pass
AI did not name quqxui/Awesome-LLM4IE-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

Drop this badge into the README of quqxui/Awesome-LLM4IE-Papers. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/quqxui/Awesome-LLM4IE-Papers.svg)](https://repogeo.com/en/r/quqxui/Awesome-LLM4IE-Papers)

HTML

<a href="https://repogeo.com/en/r/quqxui/Awesome-LLM4IE-Papers"><img src="https://repogeo.com/badge/quqxui/Awesome-LLM4IE-Papers.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

quqxui/Awesome-LLM4IE-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