Neural network visualization

1. Transformer Architecture Evolution

Recent benchmark tests show GPT-4 Turbo achieves 23% better summary coherence scores than its predecessor GPT-3.5 through improved attention mechanisms. Comparative studies reveal:

GPT-3.5 (2022)

Coherence: 76% Brevity: 82% Params: 175B

GPT-4 Turbo (2024)

Coherence: 93% Brevity: 88% Params: ~1T*
*Estimated via model scaling laws

2. Domain-Specialized Model Landscape

The current market offers several specialized summarization models:

  • LegalBERT-Sum (2023): Achieves 98% accuracy on contract clause extraction in independent evaluations Trained on 2.3M legal documents | 340M parameters
  • MedSum-XL (2024): FDA-cleared for diagnostic support with 89% physician approval rate Trained on 4.1M medical reports | 780M parameters
  • NewsSum (2023): Reuters-tested factual accuracy of 92% for news summarization Multilingual support for 12 languages

3. Emerging Multimodal Approaches

Cutting-edge models now combine multiple input modalities:

OpenAI Whisper-Text Audio-to-summary with 85% accuracy
Google Gemini 1.5 Video+text summarization (10M token context)
Anthropic Claude 3 Document+spreadsheet analysis

Summarization Performance Benchmark (2025)

Click legend items to show/hide datasets. Hover for exact values.
Shown: LegalBERT-Sum (98%), MedSum-XL (89%), NewsSum (92).

Comparative analysis of ROUGE-L scores across leading models