ENGLISH RESEARCH INFORMATION Systematized research materials produced as part of a study on gender bias in Artificial Intelligence (AI) systems and its implications for the Brazilian scientific ecosystem. The study was conducted through an integrative literature review using the OpenAlex database and covering publicati...
EVANDRO CLARO FREIRE, COUTO Weslley de Souza· Zenodo (CERN European Organi...· 0 citations
Coding agents like Claude Code and GitHub Copilot have significant implications for the way software is built and maintained in the sciences. Some of these implications center around changes in practice, such as greater or worse productivity and the need for verification practices (He et al., 2025; O'Brien, 2025a; O’Br...
Will Sutherland, Anissa Tanweer, James D. Herbsleb et al.· Zenodo (CERN European Organi...· 0 citations
Visual analytics (VA) workflows combine data transformation, feature computation, visual representation, and human interpretation, but they are usually described in prose. This hinders comparison of workflows, reuse of proven strategies, and training of novices. We present Artifact--Transform Workflow Language (ATWL),...
Natalia Andrienko, Gennady Andrienko, J\"urgen Bernard et al.· 0 citations
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Electroencephalography (EEG) underpins neuroscience, clinical neurophysiology, and brain-computer interfaces (BCIs), yet pronounced inter- and intra-subject variability limits reliability, reproducibility, and translation. This systematic review studies that quantified or modeled EEG variability across resting-state, e...
Xuan-The Tran, Thien-Nhan Vo, Son-Tung Vu et al.· 0 citations
QuAD, a framework for quantitative pre-analysis assessment of qualitative response datasets, is introduced and a content-aware multi-agent system with two-stage instruction generation and adaptive anchors to improve scoring consistency is proposed.
Wen-Shuo Zhang, Leixian Shen, Qi-Qi Zhou et al.· 0 citations
Reproducibility checks during peer review require a shared understanding of what authors'code is expected to reproduce. We present an author-in-the-loop collaborative audit that makes author declarations explicit inputs to an AI agent's investigation and assessment. A structured checklist records reproduction instructi...
Enterprise data assistants using large language models (LLMs) promise democratized data access in organizations. Yet in our real-world deployment within the CFO unit's data lake at an industry partner, we observed that business users frequently pose imperfect prompts that include domain-specific vocabulary and lack sch...
Pre-trained language models have significantly improved sentence representation learning, yet their embeddings remain sensitive to textual perturbations such as synonym substitution, masking, and word dropout. This work proposes a lightweight Contrastive Denoising Autoencoder (CDAE) that refines pre-trained BERT embedd...
Sina Heydari, Amirreza Abbasi, Mohsen Hooshmand et al.· 0 citations
As a modern commodity, language has become a vast repository of socially and psychologically significant traits and concepts, reflecting the ways people encode pattern of thoughts, behaviors, and emotions into words. Text-based Automatic Personality Prediction (APP), seeks to infer personality from linguistic behavior,...
Uncertainty estimation (UE) aims to quantify uncertainty in large language model (LLM) outputs to flag potential hallucinations and support reliable deployment. However, UE metrics often exhibit unstable performance across models and datasets, limiting their practical utility. We formalise this phenomenon as proxy fail...
Transferable attacks allow adversarial manipulations or learned attack mechanisms constructed in one setting to compromise other AI systems, potentially reducing attack costs and amplifying security and privacy risks. Yet fragmented terminology and evaluation practices hinder understanding of what transfers, why it tra...
Guangjing Wang, Ce Zhou, Yuanda Wang et al.· 0 citations
