12 papers
Personalized Safety Alignment for Text-to-Image Diffusion Models
Yu Lei, Jinbin Bai, Qingyu Shi +4
Text-to-image diffusion models have revolutionized visual content generation, yet their deployment is hindered by a fundamental limitation: safety mechanisms enforce rigid, uniform…
TRACE: Grounding Time Series in Context for Multimodal Embedding and Retrieval
Jialin Chen, Ziyu Zhao, Gaukhar Nurbek +5
The ubiquity of dynamic data in domains such as weather, healthcare, and energy underscores a growing need for effective interpretation and retrieval of time-series data. These dat…
MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
Jialin Chen, Aosong Feng, Ziyu Zhao +7
Understanding the relationship between textual news and time-series evolution is a critical yet under-explored challenge in applied data science. While multimodal learning has gain…
MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decoding
Weikang Qiu, Zheng Huang, Haoyu Hu +3
Decoding functional magnetic resonance imaging (fMRI) signals into text has been a key challenge in the neuroscience community, with the potential to advance brain-computer interfa…
Long Sequence Modeling with Attention Tensorization: From Sequence to Tensor Learning
Aosong Feng, Rex Ying, Leandros Tassiulas
As the demand for processing extended textual data grows, the ability to handle long-range dependencies and maintain computational efficiency is more critical than ever. One of the…
Hyperbolic Fine-Tuning for Large Language Models
Menglin Yang, Ram Samarth B B, Aosong Feng +4
Large language models (LLMs) have demonstrated remarkable performance across various tasks. However, it remains an open question whether the default Euclidean space is the most sui…