Sem-Detect detects AI-generated peer reviews via semantic claim comparison to multiple AI-generated versions of the same paper, achieving a 25.5% improvement in TPR at 0.1% FPR over baselines on over 20,000 ICLR and NeurIPS reviews.
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3 Pith papers cite this work, alongside 17 external citations. Polarity classification is still indexing.
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Empirical study claiming to be the first broad comparison of chunking methods in RAG, highlighting effectiveness, cost, and generalization limitations across scenarios.
DoRA generates synthetic RAG training and evaluation data from 40 defense documents, halving hallucination rates in a LoRA-adapted Llama3.1-8B compared to 8 baselines.
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Sem-Detect: Semantic Level Detection of AI Generated Peer-Reviews
Sem-Detect detects AI-generated peer reviews via semantic claim comparison to multiple AI-generated versions of the same paper, achieving a 25.5% improvement in TPR at 0.1% FPR over baselines on over 20,000 ICLR and NeurIPS reviews.
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Chunking Methods on Retrieval-Augmented Generation - Effectiveness Evaluation Against Computational Cost and Limitations
Empirical study claiming to be the first broad comparison of chunking methods in RAG, highlighting effectiveness, cost, and generalization limitations across scenarios.
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A Benchmark Construction and Evaluation Framework for Specialist Domains: Case Study on Defense-related Documents
DoRA generates synthetic RAG training and evaluation data from 40 defense documents, halving hallucination rates in a LoRA-adapted Llama3.1-8B compared to 8 baselines.