🔎 AIGC Detection

🤖 AAAI2026 · 2 paper notes

📌 Same area in other venues: 📷 CVPR2026 (7) · 🔬 ICLR2026 (30) · 💬 ACL2026 (17) · 🧪 ICML2026 (11) · 🧠 NeurIPS2025 (9)

BAID: A Benchmark for Bias Assessment of AI Detectors

This paper introduces the BAID benchmark (208K sample pairs covering 7 bias dimensions and 41 subgroups) to systematically evaluate the fairness of 4 open-source AI text detectors across demographic and linguistic subgroups, revealing significant recall disparities for dialect, informal English, and minority group texts.

Optimized Algorithms for Text Clustering with LLM-Generated Constraints

This paper proposes the LSCK-HC framework, which leverages LLMs to generate set-form must-link/cannot-link constraints (as opposed to traditional pairwise constraints), coupled with a penalty-based local search clustering algorithm. The approach achieves clustering accuracy comparable to SOTA on five short-text datasets while reducing the number of LLM queries by more than 20×.