3 papers
cs.AI2026
Should We Type or Talk to LLM Agents? A Comprehensive Study of Voice and Keyboard Input Perturbations
Zizhao Hu, Nathan Elijah Segura, Mohammad Rostami +1
Human input reaches language models by typing or speaking, and each channel leaves a distinct signature: orthographic noise for keyboards; for voice, disfluency from conventional t…
cs.CV2025
TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP
Yuliang Cai, Jesse Thomason, Mohammad Rostami
Vision-language models (VLMs), such as CLIP, have demonstrated strong performance across a range of downstream tasks. However, CLIP is still limited in negation understanding: the…
cs.LG2025
Multi-modal Synthetic Data Training and Model Collapse: Insights from VLMs and Diffusion Models
Zizhao Hu, Mohammad Rostami, Jesse Thomason
Recent research has highlighted the risk of generative model collapse, where performance progressively degrades when continually trained on self-generated data. However, existing e…