25 citations · 73 across the 36 of their papers we have counts for
5 papers · 1 filter
TRACESTEER: Trace Driven Activation Steering for Hallucination Mitigation in Diffusion Language Models
Xin Zhang, Yili Wang, Yue Tan +5
Diffusion large language models (dLLMs) have emerged as a promising alternative to autoregressive LLMs, yet remain susceptible to hallucination. Activation steering offers a promis…
DiFA: Dual Evidence Fusion and Aggregation for Token-Level Text Anomaly Detection
Yanyu Qian, Pengcheng Weng, Yue Tan +3
Text anomaly detection, the task of identifying text instances that deviate from normal language patterns, is crucial for language-driven applications. However, most existing metho…
DeMTS: Denoising Trajectories as Multivariate Time Series for Hallucination Detection in Diffusion Language Models
Xin Zhang, Yili Wang, Yue Tan +6
Diffusion large language models (D-LLMs) have emerged as a promising paradigm for text generation. However, similar to autoregressive LLMs, D-LLMs remain vulnerable to hallucinatio…
DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning
Yanyu Qian, Yue Tan, Yixin Liu +2
Diffusion large language models (D-LLMs) have emerged as a promising alternative to auto-regressive models due to their iterative refinement capabilities. However, hallucinations r…
Beyond a Single Perspective: Text Anomaly Detection with Multi-View Language Representations
Yixin Liu, Kehan Yan, Shiyuan Li +2
Text anomaly detection (TAD) plays a critical role in various language-driven real-world applications, including harmful content moderation, phishing detection, and spam review fil…