6 papers
TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models
Jaewoo Lee, Keyang Xuan, Chanakya Ekbote +3
Multimodal Large Language Models (MLLMs) have shown remarkable versatility in understanding diverse multimodal data and tasks. However, these capabilities come with an increased mo…
Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
Shujin Wu, Cheng Qian, Yi R. Fung +2
The growing capabilities of large language models (LLMs) present a key challenge of maintaining effective human oversight. Weak-to-strong generalization (W2SG) offers a promising f…
MimeQA: Towards Socially-Intelligent Nonverbal Foundation Models
Hengzhi Li, Megan Tjandrasuwita, Yi R. Fung +2
As AI becomes more closely integrated with peoples' daily activities, socially intelligent AI that can understand and interact seamlessly with humans in daily lives is increasingly…
Understanding the Emergence of Multimodal Representation Alignment
Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin +1
Multimodal representation learning is fundamentally about transforming incomparable modalities into comparable representations. While prior research primarily focused on explicitly…
VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual Cues
Jianshu Zhang, Dongyu Yao, Renjie Pi +2
Visually linking matching cues is a crucial ability in daily life, such as identifying the same person in multiple photos based on their cues, even without knowing who they are. De…
Group-Adaptive Threshold Optimization for Robust AI-Generated Text Detection
Minseok Jung, Cynthia Fuertes Panizo, Liam Dugan +4
The advancement of large language models (LLMs) has made it difficult to differentiate human-written text from AI-generated text. Several AI-text detectors have been developed in r…