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Found 6 papers, 0 papers with code
VideoDistill: Language-aware Vision Distillation for Video Question Answering
In this paper, we are inspired by the human recognition and learning pattern and propose VideoDistill, a framework with language-aware (i. e., goal-driven) behavior in both vision perception and answer generation process.
Teeth-SEG: An Efficient Instance Segmentation Framework for Orthodontic Treatment based on Anthropic Prior Knowledge
Teeth localization, segmentation, and labeling in 2D images have great potential in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health.
LLaMA-Excitor: General Instruction Tuning via Indirect Feature Interaction
LLaMA-Excitor ensures a self-adaptive allocation of additional attention to input instructions, thus effectively preserving LLMs' pre-trained knowledge when fine-tuning LLMs on low-quality instruction-following datasets.
Modeling Household Online Shopping Demand in the U.S.: A Machine Learning Approach and Comparative Investigation between 2009 and 2017
Extensive post-modeling investigation is conducted in a comparative manner between 2009 and 2017, including quantifying the importance of each input variable in predicting online shopping demand, and characterizing value-dependent relationships between demand and the input variables.
Deep Reinforcement Learning for Crowdsourced Urban Delivery: System States Characterization, Heuristics-guided Action Choice, and Rule-Interposing Integration
This paper investigates the problem of assigning shipping requests to ad hoc couriers in the context of crowdsourced urban delivery.
Deep Reinforcement Learning and Transportation Research: A Comprehensive Review
While many promising applications have been reported in the literature, there remains a lack of comprehensive synthesis of the many DRL algorithms and their uses and adaptations.
