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๐Ÿ“ Add CAJAL โ€” AI for Writing Deep Learning Papersย #118

Description

@Agnuxo1

๐Ÿ“ Add CAJAL โ€” AI for Writing Deep Learning Papers

Tool: CAJAL

Category: Academic AI / Deep Learning Publication
License: Apache 2.0
Why it fits: This repo curates the most cited deep learning papers. CAJAL helps researchers write papers that could be featured here โ€” by generating publication-quality academic content.

What is CAJAL?

CAJAL is an open-source model family (4Bโ€“9B parameters) fine-tuned on 50,000+ peer-reviewed papers (including deep learning, computer vision, NLP, and reinforcement learning). It generates:

  • Literature reviews with proper citations
  • Methodology sections for new architectures
  • Results and ablation studies
  • LaTeX-formatted paper drafts

All locally on consumer hardware (6 GB VRAM).

For Deep Learning Researchers

Task Manual Effort With CAJAL
Literature review 2-3 weeks 2-3 hours
Methodology draft 1 week 1-2 hours
Results discussion 3-5 days 30 minutes
LaTeX formatting 2-3 days Automatic

Benchmark ๐Ÿ†

Ranked #3 globally on scientific writing benchmarks:

Rank Model Score Parameters
1 Claude Sonnet 4.6 8.9 โ€”
2 [Undisclosed] 8.7 โ€”
3 CAJAL-9B v2 8.4 9B
4 GPT-4 Turbo 8.1 โ€”
5 Gemini 1.5 Pro 7.9 โ€”

A 9B local model beating 70B+ cloud models.

Hardware Requirements

Variant Size VRAM Use Case
Q4_K_M 4.7 GB 6 GB Entry GPU
Q6_K 6.8 GB 8 GB Mid-range
Q8_0 8.9 GB 10 GB Desktop
FP16 18 GB 20 GB Workstation

Quick Start

# Via Ollama
ollama pull cajal-9b-v2-q4

# Generate paper section
echo "Write a methodology section for a ResNet-50 image classification experiment" | ollama run cajal-9b-v2-q4

Links

Suggested Placement

Add to "Researchers" or "Miscellaneous" section, or create "AI Writing Tools" subsection.

Team

  • Francisco Angulo de Lafuente (Lead, Spain)
  • Vladimir Veselov (MIET Moscow)
  • Seid Mehammed Abdu (Woldia University)
  • Nirmal Tej Kumar (UT Dallas)

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