6 citations · 7 across the 10 of their papers we have counts for
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…
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs
Jiasheng Zhang, Jialin Chen, Menglin Yang +4
Dynamic text-attributed graphs (DyTAGs) are prevalent in various real-world scenarios, where each node and edge are associated with text descriptions, and both the graph structure…
From Similarity to Superiority: Channel Clustering for Time Series Forecasting
Jialin Chen, Jan Eric Lenssen, Aosong Feng +5
Time series forecasting has attracted significant attention in recent decades. Previous studies have demonstrated that the Channel-Independent (CI) strategy improves forecasting pe…
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint
Haoyue Tang, Tian Xie, Aosong Feng +3
Solving image inverse problems (e.g., super-resolution and inpainting) requires generating a high fidelity image that matches the given input (the low-resolution image or the maske…
Efficient High-Resolution Time Series Classification via Attention Kronecker Decomposition
Aosong Feng, Jialin Chen, Juan Garza +5
The high-resolution time series classification problem is essential due to the increasing availability of detailed temporal data in various domains. To tackle this challenge effect…
An Item is Worth a Prompt: Versatile Image Editing with Disentangled Control
Aosong Feng, Weikang Qiu, Jinbin Bai +5
Building on the success of text-to-image diffusion models (DPMs), image editing is an important application to enable human interaction with AI-generated content. Among various edi…
Integrating View Conditions for Image Synthesis
Jinbin Bai, Zhen Dong, Aosong Feng +3
In the field of image processing, applying intricate semantic modifications within existing images remains an enduring challenge. This paper introduces a pioneering framework that…