13 results for "air quality"
Thousands in Oregon Urged to Move Activities Indoors Over Air Quality
Oregonians were advised to curb outdoor activity after air quality was deemed "very unhealthy" amid multiple prescribed burns.…
An Intelligent Fault Diagnosis Method for General Aviation Aircraft Based on Multi-Fidelity Digital Twin and FMEA Knowledge Enhancement
Fault diagnosis of general aviation aircraft faces challenges including scarce real fault data, diverse fault types, and weak fault signatures. This paper proposes an intelligent fault diagnosis frame…
Explanation Quality Assessment as Ranking with Listwise Rewards
We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single "best" explanation token-by-token, we train reward…
Conformal PM2.5 Mapping Under Spatial Covariate Shift: Satellite-Reanalysis Fusion for Africa's Green Industrial Transition
Africa's green industrialization imperative demands reliable infrastructure for monitoring air quality. We present a satellite-reanalysis PM2.5 fusion system trained on 2,068,901 records from 404 moni…
HUD Says Realtors Can Now Speak the Truth
HUD: The U.S. Department of Housing and Urban Development (HUD) sent a “Dear Colleague” letter to real estate professionals clarifying they are not violating the Fair Housing Act when they share infor…
HUD Says It’s Legal to Tell the Truth
HUD: The U.S. Department of Housing and Urban Development (HUD) sent a “Dear Colleague” letter to real estate professionals clarifying they are not violating the Fair Housing Act when they share infor…
AI prefers resumes written by itself: Self-preferencing in Algorithmic Hiring
As artificial intelligence (AI) tools become widely adopted, large language models (LLMs) are increasingly involved on both sides of decision-making processes, ranging from hiring to content moderatio…
Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach
Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise, it remains unclear …
Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines
LLM-as-a-Judge has become the dominant paradigm for evaluating language model outputs, yet LLM judges exhibit systematic biases that compromise evaluation reliability. We present a comprehensive empir…
SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing
Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widely adopted in soccer refereeing, current AI-assis…
ClawTrace: Cost-Aware Tracing for LLM Agent Skill Distillation
Skill-distillation pipelines learn reusable rules from LLM agent trajectories, but they lack a key signal: how much each step costs. Without per-step cost, a pipeline cannot distinguish adding a missi…
STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator
The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific evaluation datasets; however, the collection of such…
XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation
Graph-based Retrieval-Augmented Generation (GraphRAG) extends traditional RAG by using knowledge graphs (KGs) to give large language models (LLMs) a structured, semantically coherent context, yielding…