59 citations · 240 across the 38 of their papers we have counts for
8 papers · 1 filter
Multi-Agent Collaborative Filtering: Orchestrating Users and Items for Agentic Recommendations
Yu Xia, Sungchul Kim, Tong Yu +2
Agentic recommendations cast recommenders as large language model (LLM) agents that can plan, reason, use tools, and interact with users of varying preferences in web applications.…
WaterFlow: Learning Fast & Robust Watermarks using Stable Diffusion
Vinay Shukla, Prachee Sharma, Ryan Rossi +3
The ability to embed watermarks in images is a fundamental problem of interest for computer vision, and is exacerbated by the rapid rise of generated imagery in recent times. Curre…
Do Large Multimodal Models Solve Caption Generation for Scientific Figures? Lessons Learned from SciCap Challenge 2023
Ting-Yao E. Hsu, Yi-Li Hsu, Shaurya Rohatgi +8
Since the SciCap datasets launch in 2021, the research community has made significant progress in generating captions for scientific figures in scholarly articles. In 2023, the fir…
From Selection to Generation: A Survey of LLM-based Active Learning
Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie +31
Active Learning (AL) has been a powerful paradigm for improving model efficiency and performance by selecting the most informative data points for labeling and training. In recent…
Mitigating Visual Knowledge Forgetting in MLLM Instruction-tuning via Modality-decoupled Gradient Descent
Junda Wu, Yuxin Xiong, Xintong Li +9
Recent MLLMs have shown emerging visual understanding and reasoning abilities after being pre-trained on large-scale multimodal datasets. Unlike pre-training, where MLLMs receive r…
Interactive Visualization Recommendation with Hier-SUCB
Songwen Hu, Ryan A. Rossi, Tong Yu +4
Visualization recommendation aims to enable rapid visual analysis of massive datasets. In real-world scenarios, it is essential to quickly gather and comprehend user preferences to…
Understanding How Paper Writers Use AI-Generated Captions in Figure Caption Writing
Ho Yin, Ng, Ting-Yao Hsu +6
Figures and their captions play a key role in scientific publications. However, despite their importance, many captions in published papers are poorly crafted, largely due to a lac…
Multi-LLM Collaborative Caption Generation in Scientific Documents
Jaeyoung Kim, Jongho Lee, Hong-Jun Choi +8
Scientific figure captioning is a complex task that requires generating contextually appropriate descriptions of visual content. However, existing methods often fall short by utili…