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When the Target Domain Changes: AI-Mediated Construct Drift in High-Stakes English Language AssessmenW
Jul 13, 2026Yi GuiComputerized Adaptive Testing Interpretive Openness
SAT-RTS: A systematic framework for tactical knowledge extraction and visualization-based analysis in real-time strategy games
Jun 29, 2026Chunhui Bai, Changhe Li, Yuqiang Li +2Visual Analytics
GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets
Jun 26, 2026Janak M. Patel, Anirudh Deodhar, Dagnachew BirruDemand Forecasting Long-Horizon Forecasting
What's in an Earth Embedding? An Explainability Analysis of Location Encoders
Jun 23, 2026Livia Betti, Sebastian Ricke, Ivica Obadic +2Spatial Representation Implicit Neural Representations
Artificial collectives of specialists and generalists excel at different tasks
Jun 18, 2026John Meluso, Laurent Hébert-Dufresne, Christoph Riedl +1Multi-Agent Systems Collective Behaviors
How Transparent is DiffusionGemma?
Jun 18, 2026Joshua Engels, Callum McDougall, Bilal Chughtai +11Transparency Interpretable Models
Multimodal Concept Bottleneck Models
Jun 18, 2026Tongqing Shi, Ge Yan, Tuomas Oikarinen +1Concept Bottleneck Models Model Interpretability
HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice
Jun 16, 2026Noah J. Kim-Baumann, Torsten HiltmannHievi-Rag History
A Bayesian Boolean Matrix Factorization with Application to Copy Number Analysis in Cancer
Jun 16, 2026Adolphus Wagala, Mehmet Samur, Giovanni ParmigianiCancer Genome Atlas Matrix Factorization
We Need Explanation Cards to Connect Explanation Algorithms to the Real World
Jun 15, 2026Eric Günther, Balázs Szabados, Kristof Meding +3Explainability Counterfactual Explanation
Graphical conditional generative modeling for digital twin modeling
Jun 15, 2026Zongren Zou, Théo Bourdais, Ricardo Baptista +1Surrogate Models Generative Models
DifFRACT: Diffusion Feature Reconstruction and Attribution for Circuit Tracing
Jun 14, 2026Artyom Mazur, Nina Konovalova, Aibek AlanovMultimodal Diffusion Transformers Multimodal Transformers
Measuring Human Value Expression in Social Media Texts: Calibrated LLM Annotation and Encoder Transfer
Jun 9, 2026Maria Milkova, Maksim RudnevHuman Values Human Annotators
A systematic investigation of molecular encoding methods for drug property predictions across neural network and Transformer encoder-based model
Jun 8, 2026Sheng-Ya Chen, Shan-Ju YehMolecular Property Prediction Mechanistic Interpretability
Sparsely gated tiny linear experts
Jun 5, 2026Simon SchugFeed-Forward Network Transformer Layers
Physics-Driven Semantic Scattering Structure Understanding of Aircraft Target in SAR Images
Jun 5, 2026Yifei Yin, Xiaogang Yu, Hao Shi +2Synthetic Aperture Radar Speckle
Trajectory Dynamics in Language Model Hidden States Predict Human Processing Costs Beyond Surprisal
Jun 3, 2026Elan BarenholtzSurprisal Hidden States
Ablating Archetypes: The Stability of Archetypal SAEs is an Artifact of Initialization and Metric Design
Jun 1, 2026Michał Brzozowski, Neo Christopher ChungImproving Sparse Autoencoders Unsupervised Dictionary Learning
When Models Disagree: Rethinking LLM Evaluation for Public Comment Analysis
May 27, 2026Aisha Najera, Alvin Moon, Vedant Srinivasan +1Large Language Model Evaluation Inter-Rater Variability
ProtoPathway: Biologically Structured Prototype-Pathway Fusion for Multimodal Cancer Survival Prediction
May 20, 2026Amaya Gallagher-Syed, Costantino Pitzalis, Myles J. Lewis +2Cancer Genome Atlas Multimodal Clinical Data
BCI-sift: An automated feature selection toolbox for Brain Computer Interface applications
May 19, 2026Elena C Offenberg, Dirk Keller, Mariska J Vansteensel +3Brain-Computer Interface Feature Selection
Cross-Paradigm Knowledge Distillation: A Comprehensive Study of Bidirectional Transfer Between Random Forests and Deep Neural Networks for Big Data Applications
May 19, 2026Mahdi Naser MoghadasiRandom Forest Knowledge Distillation
Learning Normal Representations for Blood Biomarkers
May 18, 2026Aashna P. Shah, Michelle M. Li, Yash Lal +9Biomarker Populations
Event-Grounded Sparse Autoencoders for Vision-Language-Action Policies
May 17, 2026Xinchen Jin, Aditya Chatterjee, Pranav Kumar +1Vision-Language-Action Models Improving Sparse Autoencoders
SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning
May 16, 2026Yongfeng Huang, Ruiying Chen, James ChengHievi-Rag Clinical Reasoning
Can We Trust AI-Inferred User States. A Psychometric Framework for Validating the Reliability of Users States Classification by LLMs in Operational Environments
May 15, 2026Izabella Krzeminska, Michal Butkiewicz, Ewa KomkowskaLarge Language Model Reliability Psychometrics
Rethinking Layer Relevance in Large Language Models Beyond Cosine Similarity
May 13, 2026Cristian Hinostroza, Rodrigo Toro Icarte, Christ Devia +4Large Language Model Performance Cosine Similarity
Towards Effective Theory of LLMs: A Representation Learning Approach
May 10, 2026Muhammed Ustaomeroglu, Guannan QuModel Interpretability Representation Learning
Neurosymbolic Framework for Concept-Driven Logical Reasoning in Skeleton-Based Human Action Recognition
May 8, 2026Talha Ilyas, Deval Mehta, Zongyuan GeSkeleton-Based Action Recognition Temporal Action Localization
An Explainable Unsupervised-to-Supervised Machine Learning Framework for Dietary Pattern Discovery Using UK National Dietary Survey Data
May 7, 2026Wing Yi Yu, Chun Yin ChiuNutrient Reasoning Clinical Prediction

Jul 13, 2026 · cs.CLJ/K move · Enter open · S save

When the Target Domain Changes: AI-Mediated Construct Drift in High-Stakes English Language AssessmenW

Yi Gui

Measurement Incorporated

High-stakes English proficiency tests treat standardized, unaided performance as evidence for score interpretations about academic English proficiency. This interpretation remains meaningful, but as target language use domains increasingly involve generative AI, the extrapolation from unaided test performance to academic communicative readiness becomes less self-evident. This conceptual validity argument reframes AI as a score-interpretation problem in high-stakes language testing, not only an operational issue of scoring, feedback, security, or misconduct. Synthesizing current literature in three uneven layers, the paper shows that most work treats AI as assessment infrastructure, while far less theorizes its implications for construct validity and extrapolation warrants. It defines AI-mediated construct drift as the misalignment that arises when communicative abilities required in the target domain change through AI mediation while test constructs remain anchored to an unaided-performance model. It proposes bounded AI mediation as a validity-oriented design principle: a standardized condition in which all test takers access the same institutionally controlled AI assistant, with predefined assistance boundaries, logged interactions, and tasks that distinguish comprehension support from answer generation. The paper argues that score interpretations should be narrowed and supplemented when used to support claims about AI-mediated academic communication.

Computerized Adaptive Testing Interpretive Openness Artificial Intelligence Evaluation High-Stakes Decision Mediation Target Domain Data Generation

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