8 citations · 8 across the 4 of their papers we have counts for
7 papers
Fast SAM2 with Text-Driven Token Pruning
Avilasha Mandal, Chaoning Zhang, Fachrina Dewi Puspitasari +6
Segment Anything Model 2 (SAM2), a vision foundation model has significantly advanced in prompt-driven video object segmentation, yet their practical deployment remains limited by…
GeoRef: Referring Expressions in Geometry via Task Formulation, Synthetic Supervision, and Reinforced MLLM-based Solutions
Bing Liu, Wenqiang Yv, Xuzheng Yang +6
AI-driven geometric problem solving is a complex vision-language task that requires accurate diagram interpretation, mathematical reasoning, and robust cross-modal grounding. A fou…
Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy
Yiting Yang, Hao Luo, Yuan Sun +7
A prevalent approach in Parameter-Efficient Fine-Tuning (PEFT) of pre-trained Vision Transformers (ViT) involves freezing the majority of the backbone parameters and solely learnin…
MSCRS: Multi-modal Semantic Graph Prompt Learning Framework for Conversational Recommender Systems
Yibiao Wei, Jie Zou, Weikang Guo +3
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations by interacting with users through conversations. Most existing studies of CRS focus on extract…
Syzygy of Thoughts: Improving LLM CoT with the Minimal Free Resolution
Chenghao Li, Chaoning Zhang, Yi Lu +7
Chain-of-Thought (CoT) prompting enhances the reasoning of large language models (LLMs) by decomposing problems into sequential steps, mimicking human logic and reducing errors. Ho…
New Dataset and Methods for Fine-Grained Compositional Referring Expression Comprehension via Specialist-MLLM Collaboration
Xuzheng Yang, Junzhuo Liu, Peng Wang +3
Referring Expression Comprehension (REC) is a foundational cross-modal task that evaluates the interplay of language understanding, image comprehension, and language-to-image groun…