large language models

VLM-Mapper: Multimodal vision-language models for prior guided lane-level HD map construction

The automated construction of High-Definition (HD) maps from remote sensing data is essential for modern intelligent transportation systems and spatial data infrastructure. While imagery provides a scalable solution for lane-level HD map construction, traditional discriminative models often struggle in complex scenario...

RECUR: Retrieval-Based customer review analysis framework utilizing nonparametric masked language modeling

Social simulations with large language model risk Utopian illusion

Reliable simulation of human behaviour is essential for explaining, predicting, and intervening in our society. Recent advances in large language models (LLMs) have shown promise in emulating human behaviours, interactions, and decision-making, offering a powerful new lens for social science studies. However, the exten...

Human-like content analysis for generative AI with language-grounded sparse encoders

The rapid development of generative AI has transformed content creation, communication, and human development. However, this technology raises profound concerns in high-stakes domains, demanding rigorous methods to analyze and evaluate AI-generated content. While existing analytic methods often treat images as indivisi...

CyberRoBERTa: A Lightweight Transformer-Based Language Model for IoT Intrusion Detection

CyberRoBERTa is presented, built specifically to test whether departing from off-the-shelf LLM components, through a domain-specific Unigram tokenizer and an IoT-specialized data collator, yields a genuine advantage for IoT intrusion detection.

Research on Model Construction of Intelligent Command and Control System Based on Large Language Model

Retrofitting language models to operate over bytes.

Recent advances in artificial intelligence (AI) have largely been driven by large language models, deep neural networks that operate over discrete units called tokens. To represent text, most large language models use words or word fragments as the tokens, known as subword tokenization1. Subword tokenization obscures f...

Beyond the prompt for pedestrian traffic and crowd behavior management: PedAgent, a Large Language Model empowered Agent with an integrated simulating-analyzing-optimizing functional chain

Efficient VLM Inference System With LoRA Adapters at the Edge

Vision Language Models (VLMs) extend large language models with visual perception, enabling complex vision tasks at the edge. Low-rank adaptation (LoRA) adapters offer a lightweight method to inject domain-specific knowledge into a shared base VLM, making them attractive for edge serving where concurrent mobile clients...

DWI: Efficient On-Device LLM Decoding Through Dynamic Width Selection on Nested Models

Deploying large language models (LLMs) on resource-constrained mobile devices remains a significant challenge due to memory limitations and high I/O overhead. While existing dynamic sparsity methods reduce computation costs, they often suffer from inefficient loading patterns that degrade I/O throughput. To address thi...

Adaptive Code Generation for Controlling Robots

Deploying robots as Complex Adaptive Systems (CAS) in unknown and dynamic environments necessitates a transition from rigid command libraries toward intention-based autonomy, as natural language represents the only medium capable of articulating complex goals beyond the capacity of finite instruction sets. While Large...

Enhancing large language model navigation via two-stage fine-tuning and sparse-reward reinforcement learning