Academic reviewing gets an AI sidekick that annotates papers but leaves critical thinking to humans
https://arxiv.org/abs/2412.00281
🎯 Original Problem:
Academic peer review faces a massive workload crisis with reviewers spending over 15 million hours annually reviewing manuscripts. Each reviewer handles about 14 manuscripts yearly, spending 5 hours per review, often leading to hasty assessments.
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🔧 Solution in this Paper:
→ AnnotateGPT integrates GPT-4 into manuscript review through intelligent annotation rather than full automation.
→ The system highlights relevant excerpts based on specific review criteria like originality, relevance, and rigor.
→ Reviewers maintain control by fact-checking AI annotations and adding their own insights.
→ The platform compiles annotations into structured reviews organized by criteria or sentiment.
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💡 Key Insights:
→ LLMs excel at identifying relevant information but struggle with high-level analysis
→ Annotation-based interaction proves more effective than traditional chat interfaces
→ Color-coding annotations by review criteria improves reviewer focus and comprehension
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📊 Results:
→ Technology Acceptance Model evaluation with 9 participants showed strong construct validity (Cronbach's α: 0.8-0.83)
→ Users rated AnnotateGPT highly for improving focus and maintaining review criteria consistency
→ System demonstrated seamless integration with existing PDF viewer workflows
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