111 citations · 282 across the 52 of their papers we have counts for
60 papers
Can We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators
Xinyu Chen, Adnan Mahmood, Mark Dras
Video-language models and video agents can produce hallucinations that conflict with spatiotemporal evidence. Existing benchmarks mainly evaluate model hallucinations, and heteroge…
Process-Constituted Intelligence: A Shared Criterion for Humans and Machines
Michael J. Richardson, Ayeh Alhasan, Cassandra Crone +5
Intelligence is constituted by \textit{process} (iterative activity through which output emerges), not in the output itself. Generative AI (GenAI) is trained on \textit{traces} (te…
Beyond Shallow Alignment: How Post-Training Methods Determine Refusal Circuits And Steering Robustness
Hoang Cuong Nguyen, Mark Dras, Usman Naseem
How do the methods used to train language models to refuse harmful requests shape how that refusal actually works inside the model? We compare three post-training methods - supervi…
AlignCultura: Towards Culturally Aligned Large Language Models?
Gautam Siddharth Kashyap, Mark Dras, Usman Naseem
Cultural alignment in Large Language Models (LLMs) is essential for producing contextually aware, respectful, and trustworthy outputs. Without it, models risk generating stereotype…
Beyond Theoretical Bounds: Empirical Privacy Loss Calibration for Text Rewriting Under Local Differential Privacy
Weijun Li, Arnaud Grivet Sébert, Qiongkai Xu +2
The growing use of large language models has increased interest in sharing textual data in a privacy-preserving manner. One prominent line of work addresses this challenge through…
Facial Movement Dynamics Reveal Workload During Complex Multitasking
Carter Sale, Melissa N. Stolar, Gaurav Patil +8
Real-time cognitive workload monitoring is crucial in safety-critical environments, yet established measures are intrusive, expensive, or lack temporal resolution. We tested whethe…