Artificial intelligence (AI) is transforming human resource management (HRM), yet the cognitive and psychological factors associated with human resource (HR) professionals’ intentions to use AI remain incompletely understood. Drawing on the Technology Acceptance Model (TAM) and appraisal perspectives, this study ex...
René Arseneault, Houssem Eddine Ben Messaoud· Journal of Enterprise Inform...· 0 citations
This study examines collaborative learning design with a generative artificial intelligence (GenAI) co-pilot among in-service university English teachers in China. In a between-subjects experiment ( N = 60), epistemic network analysis (ENA) was used to model the situated discourse structures of team dialogues, compleme...
Yanyi Wu· Teaching and Teacher Educati...· 0 citations
This article discusses the benefits and challenges of using artificial intelligence in academic writing. It explains how AI can help teachers and students improve texts, correct grammar, and organize ideas while stressing the need to verify information and use AI responsibly.
Raykhan Bakhadir kizi Oteshova· Zenodo (CERN European Organi...· 0 citations
Phenotyping is fundamental to rare disease diagnosis, but manually curating structured phenotypes from clinical notes is labor intensive and difficult to scale. Existing artificial intelligence (AI) approaches optimize individual components of phenotyping but generally do not operationalize the full workflow of extract...
Cathy Shyr, Yan Hu, Rory J Tinker et al.· npj Digital Medicine· 0 citations
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Circuit extraction identifies model components whose presence preserves a target behavior under ablation, but preserving behavior does not single out one circuit. We study this in a synthetic Lean tactic-prediction benchmark with fixed proof rules and randomized surface form. Across dense and weight-sparse checkpoints...
The most prevalent distributed systems today include people and their personal machines (smartphones), and computations in them are driven by people's volitions. Volition-guarded multiagent atomic transactions were proposed as an abstract specification language for such systems, in which a transaction has a preconditio...
An inference-time intervention that masks feed-forward network activation coordinates while keeping pretrained weights fixed provides a task-dependent intervention surface, with causal mechanisms, equal-budget advantages, repeated-run uncertainty, and serving cost still open.
Sheng Xu, Zhen Chen, Jun-Hua Wang et al.· 0 citations
This paper investigates over-the-air federated learning (AirFL) in wireless systems where the access point is equipped with a multi-waveguide pinching antenna system (PASS). We adopt the widely studied learning-oriented AirFL formulation, which seeks to maximize the number of selected devices while keeping the aggregat...
Seyed Mohammad Azimi-Abarghouyi, Christopher G. Brinton· 0 citations
This work derives a Latent Consistent Proximal (LCP) solver that evolves each latent variable from its previous state rather than reconstructing through an indirect residual, and stabilizes small target updates through task-adaptive normalization and gain control.
Tianfang Zhang, Feng-Yi Wu, Lei Li et al.· arXiv.org· 0 citations
Memory has emerged as a cornerstone of modern LLM-based agents, supporting their evolution from single-turn assistants to long-term collaborators. However, memory is not always beneficial: retrieved memories often induce a critical issue of sycophancy, causing agents to over-align with the user at the cost of factual a...
Zhishang Xiang, Zerui Chen, Yunbo Tang et al.· 0 citations
Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs are susceptible to the same cognitive heuristics that bias human judgment. Yet, no work has investigated whether these heuristics affect a model's assessment of code vulne...
Asif Shahriar, Hongyu Cai, Hadjer Benkraouda et al.· 0 citations
