393 citations · 694 across the 19 of their papers we have counts for
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cs.CV2024★ 3 cited
Mitigating Object Hallucination in MLLMs via Data-augmented Phrase-level Alignment
Pritam Sarkar, Sayna Ebrahimi, Ali Etemad +3
Despite their significant advancements, Multimodal Large Language Models (MLLMs) often generate factually inaccurate information, referred to as hallucination. In this work, we add…
cs.HC2024★ 9 cited
CLARE: Cognitive Load Assessment in REaltime with Multimodal Data
Anubhav Bhatti, Prithila Angkan, Behnam Behinaein +11
We present a novel multimodal dataset for Cognitive Load Assessment in REal-time (CLARE). The dataset contains physiological and gaze data from 24 participants with self-reported c…