2 papers
cs.CV2026
See, Hear, and Understand: Benchmarking Audiovisual Human Speech Understanding in Multimodal Large Language Models
Le Thien Phuc Nguyen, Zhuoran Yu, Samuel Low Yu Hang +8
Multimodal large language models (MLLMs) are expected to jointly interpret vision, audio, and language, yet existing video benchmarks rarely assess fine-grained reasoning about hum…
cs.CV2024
CoAPT: Context Attribute words for Prompt Tuning
Gun Lee, Subin An, Sungyong Baik +1
We propose a novel prompt tuning method called CoAPT(Context Attribute words in Prompt Tuning) for few/zero-shot image classification. The core motivation is that attributes are de…