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20142024
most citedDDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models

15 citations · 21 across the 12 of their papers we have counts for

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11 papers · 1 filter

cs.CV2024

Plain-Det: A Plain Multi-Dataset Object Detector

Cheng Shi, Yuchen Zhu, Sibei Yang

Recent advancements in large-scale foundational models have sparked widespread interest in training highly proficient large vision models. A common consensus revolves around the ne…

cs.CV2024

Curriculum Point Prompting for Weakly-Supervised Referring Image Segmentation

Qiyuan Dai, Sibei Yang

Referring image segmentation (RIS) aims to precisely segment referents in images through corresponding natural language expressions, yet relying on cost-intensive mask annotations.…

cs.CV20241 cited

The devil is in the object boundary: towards annotation-free instance segmentation using Foundation Models

Cheng Shi, Sibei Yang

Foundation models, pre-trained on a large amount of data have demonstrated impressive zero-shot capabilities in various downstream tasks. However, in object detection and instance…

cs.CV202315 cited

DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models

Ge Zheng, Bin Yang, Jiajin Tang +2

A long-standing goal of AI systems is to perform complex multimodal reasoning like humans. Recently, large language models (LLMs) have made remarkable strides in such multi-step re…

cs.CV2023

LoGoPrompt: Synthetic Text Images Can Be Good Visual Prompts for Vision-Language Models

Cheng Shi, Sibei Yang

Prompt engineering is a powerful tool used to enhance the performance of pre-trained models on downstream tasks. For example, providing the prompt "Let's think step by step" improv…

cs.CV2023

Temporal Collection and Distribution for Referring Video Object Segmentation

Jiajin Tang, Ge Zheng, Sibei Yang

Referring video object segmentation aims to segment a referent throughout a video sequence according to a natural language expression. It requires aligning the natural language exp…