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Add AI-generated text detection benchmarks to Evaluation and Benchmarks #414

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Expand Up @@ -710,6 +710,11 @@ NLU and cross-lingual:
- [MTEB](https://github.com/embeddings-benchmark/mteb) - Massive Text Embedding Benchmark; standard for sentence/document encoders.
- [BEIR](https://github.com/beir-cellar/beir) - heterogeneous IR benchmark for retrieval models.

AI-generated text detection:

- [RAID](https://github.com/liamdugan/raid) - large adversarial benchmark for AI-generated text detectors across generators, domains, and attacks.
- [AI2Human Detection Benchmark](https://github.com/chajahmed/ai2human-detection-benchmark) - labeled corpus of raw-AI, human, and humanized (paraphrase-tool and LLM-humanizer) text samples, with a script to score against a live detector API.

Modern LM evaluation (2023-2026):

- [HELM](https://crfm.stanford.edu/helm/) - holistic evaluation across NLP tasks, accuracy and beyond.
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