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Found 15 papers, 4 papers with code
Event-Priori-Based Vision-Language Model for Efficient Visual Understanding
Its core contribution is a novel mechanism leveraging motion priors derived from dynamic event vision to enhance VLM efficiency.
Towards Intelligent Edge Sensing for ISCC Network: Joint Multi-Tier DNN Partitioning and Beamforming Design
To minimize the overall sensing task inference latency across all ISAC devices, we jointly optimize the DNN partitioning strategy, ISAC beamforming, and computational resource allocation at the MEC servers and devices, subject to sensing beampattern constraints.
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models
Neural Networks (NNs) trained through supervised learning struggle with managing edge-case scenarios common in real-world driving due to the intractability of exhaustive datasets covering all edge-cases, making knowledge-driven approaches, akin to how humans intuitively detect unexpected driving behavior, a suitable complement to data-driven methods.
Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling
Cross-domain recommendation (CDR) is a task that aims to improve the recommendation performance in a target domain by leveraging the information from source domains.
RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms
This hybrid approach leverages the reliability and interpretability of PP while using RL to fine-tune the controller's performance in real-world scenarios.
Mitigating Social Bias in Large Language Models: A Multi-Objective Approach within a Multi-Agent Framework
Our experiments conducted on two datasets and two models demonstrate that MOMA reduces bias scores by up to 87. 7%, with only a marginal performance degradation of up to 6. 8% in the BBQ dataset.
Learning to Drift in Extreme Turning with Active Exploration and Gaussian Process Based MPC
In the RC car experiment, the average lateral error with GPR is 36. 7% lower, and exploration further leads to a 29. 0% reduction.
Mini Honor of Kings: A Lightweight Environment for Multi-Agent Reinforcement Learning
To address these issues, we introduce the first publicly available map editor for the popular mobile game Honor of Kings and design a lightweight environment, Mini Honor of Kings (Mini HoK), for researchers to conduct experiments.
Attention and Prediction Guided Motion Detection for Low-Contrast Small Moving Targets
The developed visual system comprises three main subsystems, namely, an attention module, an STMD-based neural network, and a prediction module.
A Time-Delay Feedback Neural Network for Discriminating Small, Fast-Moving Targets in Complex Dynamic Environments
Discriminating small moving objects within complex visual environments is a significant challenge for autonomous micro robots that are generally limited in computational power.
An LGMD Based Competitive Collision Avoidance Strategy for UAV
In this paper, we present an LGMD based competitive collision avoidance method for UAV indoor navigation.
Synthetic Neural Vision System Design for Motion Pattern Recognition in Dynamic Robot Scenes
The presented system is a synthetic neural network, which comprises two complementary sub-systems with four spiking neurons -- the lobula giant movement detectors (LGMD1 and LGMD2) in locusts for sensing looming and recession, and the direction selective neurons (DSN-R and DSN-L) in flies for translational motion extraction.
Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review
A good number of motion detectors have been identified in the insects' visual pathways.
A Bio-inspired Collision Detecotr for Small Quadcopter
The observed results from the experiments demonstrated that the LGMD collision detector is feasible to work as a vision module for the quadcopter's collision avoidance task.
Collision Selective Visual Neural Network Inspired by LGMD2 Neurons in Juvenile Locusts
The results demonstrated this framework is able to detect looming dark objects embedded in bright backgrounds selectively, which make it ideal for ground mobile platforms.
