3 papers
cs.CL2026
Orthographic Constraint Satisfaction and Human Difficulty Alignment in Large Language Models
Bryan E. Tuck, Rakesh M. Verma
Large language models must satisfy hard orthographic constraints during controlled text generation, yet systematic cross-family evaluation remains limited. We evaluate 39 configura…
cs.LG2026
Guided Perturbation Sensitivity (GPS): Detecting Adversarial Text via Embedding Stability and Word Importance
Bryan E. Tuck, Rakesh M. Verma
Adversarial text attacks remain a persistent threat to transformer models, yet existing defenses are typically attack-specific or require costly model retraining, leaving a gap for…
cs.CL2025
Unmasking the Imposters: How Censorship and Domain Adaptation Affect the Detection of Machine-Generated Tweets
Bryan E. Tuck, Rakesh M. Verma
The rapid development of large language models (LLMs) has significantly improved the generation of fluent and convincing text, raising concerns about their potential misuse on soci…