4 papers
How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms
Shengji Jin, Yuanhao Zou, Victor Zhu +2
While Multimodal Large Language Models (MLLMs) have advanced Video Temporal Grounding (VTG), existing methods often couple output paradigms with different backbones, datasets, and…
Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach
Param Kulkarni, Yingchi Liu, Hao-Ming Fu +8
Achieving a delicate balance between fostering trust in law enforcement and protecting the rights of both officers and civilians continues to emerge as a pressing research and prod…
DHP Benchmark: Are LLMs Good NLG Evaluators?
Yicheng Wang, Jiayi Yuan, Yu-Neng Chuang +7
Large Language Models (LLMs) are increasingly serving as evaluators in Natural Language Generation (NLG) tasks; this is often referred to as ``LLM-as-a-judge'' paradigm. However, t…
FairLENS: Assessing Fairness in Law Enforcement Speech Recognition
Yicheng Wang, Mark Cusick, Mohamed Laila +7
Automatic speech recognition (ASR) techniques have become powerful tools, enhancing efficiency in law enforcement scenarios. To ensure fairness for demographic groups in different…