16 citations · 38 across the 16 of their papers we have counts for
6 papers · 1 filter
Rethinking Agentic Workflows: Evaluating Inference-Based Test-Time Scaling Strategies in Text2SQL Tasks
Jiajing Guo, Kenil Patel, Jorge Piazentin Ono +2
Large language models (LLMs) are increasingly powering Text-to-SQL (Text2SQL) systems, enabling non-expert users to query industrial databases using natural language. While test-ti…
ViT-Split: Unleashing the Power of Vision Foundation Models via Efficient Splitting Heads
Yifan Li, Xin Li, Tianqin Li +3
Vision foundation models (VFMs) have demonstrated remarkable performance across a wide range of downstream tasks. While several VFM adapters have shown promising results by leverag…
VISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels
Xiwei Xuan, Xiaoqi Wang, Wenbin He +4
The advances in multi-modal foundation models (FMs) (e.g., CLIP and LLaVA) have facilitated the auto-labeling of large-scale datasets, enhancing model performance in challenging do…
ProSAM: Enhancing the Robustness of SAM-based Visual Reference Segmentation with Probabilistic Prompts
Xiaoqi Wang, Clint Sebastian, Wenbin He +1
The recent advancements in large foundation models have driven the success of open-set image segmentation, a task focused on segmenting objects beyond predefined categories. Among…
DINO-R1: Incentivizing Reasoning Capability in Vision Foundation Models
Chenbin Pan, Wenbin He, Zhengzhong Tu +1
The recent explosive interest in the reasoning capabilities of large language models, such as DeepSeek-R1, has demonstrated remarkable success through reinforcement learning-based…
InterChat: Enhancing Generative Visual Analytics using Multimodal Interactions
Juntong Chen, Jiang Wu, Jiajing Guo +6
The rise of Large Language Models (LLMs) and generative visual analytics systems has transformed data-driven insights, yet significant challenges persist in accurately interpreting…