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Bridging the Gap in Proactive Assistance As large language models evolve into personal assistant agents, they are increasingly expected to handle complex, lo...
What the paper is about Large language models often suffer from fact loss, timeline confusion, persona drift, and reduced stability during long-range interac...
Small, Private Language Models as Teammates for Educational Assessment Design explores how different types of artificial intelligence can assist educators in...
BiFedKD: Bidirectional Federated Knowledge Distillation Framework for Non-IID and Long-Tailed ECG Monitoring This research addresses the challenge of trainin...
Large Language Models (LLMs) are increasingly used to synthesize complex scientific information, yet we lack a clear understanding of how well these models p...
This research addresses a fundamental challenge in artificial intelligence: how to maintain consistent reasoning when knowledge bases are updated.
A Deterministic Agentic Workflow for HS Tariff Classification: Multi-Dimensional Rule Reasoning with Interpretable Decisions The Harmonized System (HS) is th...
Probabilistic Verification of Recurrent Neural Networks for Single and Multi-Agent Reinforcement Learning introduces a new framework called RNN-ProVe designe...
AI Outperforms Humans in Personalized Image Aesthetics Assessment via LLM-Based Interviews and Semantic Feature Extraction This research addresses the challe...
Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG This research investigates the reliability of citations in Agentic GraphRAG sy...
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