Papers
1–3 of 3Research Paper·Jan 29, 2026
Learn-to-Distance: Distance Learning for Detecting LLM-Generated Text
Modern large language models (LLMs) such as GPT, Claude, and Gemini have transformed the way we learn, work, and communicate. Yet, their ability to produce highly human-like text raises serious concer...
7.0 viability
Research Paper·Mar 18, 2026
Detecting the Machine: A Comprehensive Benchmark of AI-Generated Text Detectors Across Architectures, Domains, and Adversarial Conditions
The rapid proliferation of large language models (LLMs) has created an urgent need for robust and generalizable detectors of machine-generated text. Existing benchmarks typically evaluate a single det...
5.0 viability
Research Paper·Feb 19, 2026
Towards Anytime-Valid Statistical Watermarking
The proliferation of Large Language Models (LLMs) necessitates efficient mechanisms to distinguish machine-generated content from human text. While statistical watermarking has emerged as a promising ...
5.0 viability