8 papers
Hummus: A Dataset of Humorous Multimodal Metaphor Use
Xiaoyu Tong, Zhi Zhang, Pia Sommerauer +2
Metaphor and humor share a lot of common ground, and metaphor is one of the most common humorous mechanisms. This study focuses on the humorous capacity of multimodal metaphors, wh…
NeuroAda: Activating Each Neuron's Potential for Parameter-Efficient Fine-Tuning
Zhi Zhang, Yixian Shen, Congfeng Cao +1
Existing parameter-efficient fine-tuning (PEFT) methods primarily fall into two categories: addition-based and selective in-situ adaptation. The former, such as LoRA, introduce add…
Lightweight MSA Design Advances Protein Folding From Evolutionary Embeddings
Hanqun Cao, Xinyi Zhou, Zijun Gao +7
Protein structure prediction often hinges on multiple sequence alignments (MSAs), which underperform on low-homology and orphan proteins. We introduce PLAME, a lightweight MSA desi…
Never compromise with vulnerabilities: a comprehensive survey on AI governance
Yuchu Jiang, Jian Zhao, Yuchen Yuan +64
The rapid advancement of AI has expanded its capabilities across domains, yet introduced critical technical vulnerabilities, such as algorithmic bias and adversarial sensitivity, t…
Cross-modal Information Flow in Multimodal Large Language Models
Zhi Zhang, Srishti Yadav, Fengze Han +1
The recent advancements in auto-regressive multimodal large language models (MLLMs) have demonstrated promising progress for vision-language tasks. While there exists a variety of…
SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning
Gaole Dai, Chun-Kai Fan, Yiming Tang +7
Advances in Parameter-Efficient Fine-Tuning (PEFT) bridged the performance gap with Full Fine-Tuning (FFT) through sophisticated analysis of pre-trained parameter spaces. Starting…