A persistent accuracy ceiling in automated verbal deception detection

arXiv:2610.12118 · cs.CL · Submitted 2026-10-08 · Read on arXiv

cs.CL

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Accuracy — 62× in this paper · explained in 1 episode
• Transformer — 20× in this paper · explained in 2 episodes
• Embeddings — 17× in this paper · explained in 2 episodes
• Association for Computational Linguistics — 15× in this paper
• Active Learning — 8× in this paper · explained in 6 episodes
• Foundation Model — 6× in this paper · explained in 3 episodes
• Feature Selection — 5× in this paper · explained in 4 episodes
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Verifiability — 4× in this paper · explained in 2 episodes
• Ensemble Learning — 3× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Predictive Modeling — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Cognitive Load — 2× in this paper · explained in 2 episodes
• Concept Drift — 2× in this paper · explained in 4 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• European Intelligence and Security Informatics Conference — 2× in this paper
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• International Conference on Natural Language Processing — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Multimodal Fusion — 2× in this paper · explained in 3 episodes
• Open Science Framework — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Transformer Models — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Accountability — 1× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial Training — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Causal Inference — 1× in this paper · explained in 4 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 1× in this paper
• Explainability — 1× in this paper · explained in 3 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Methodological Rigor — 1× in this paper · explained in 2 episodes
• Parsimony — 1× in this paper · explained in 2 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes

Sources

• Effects of Soft-Domain Transfer and Named Entity Information on Deception Detection
• Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysis
• PU-Lie: Lightweight Deception Detection in Imbalanced Diplomatic Dialogues via Positive-Unlabeled Learning
• Deception Detection in Videos
• Advancing Automated Deception Detection: A Multimodal Approach to Feature Extraction and Analysis
• Voting-based Multimodal Automatic Deception Detection
• The Mafiascum Dataset: A Large Text Corpus for Deception Detection
• What if Deception Cannot be Detected? A Cross-Linguistic Study on the Limits of Deception Detection from Text
• Exploring Machine Learning and Transformer-based Approaches for Deceptive Text Classification: A Comparative Analysis
• Unmasking Falsehoods in Reviews: An Exploration of NLP Techniques
• Voting for Deceptive Opinion Spam Detection
• Fraud detection in telephone conversations for financial services using linguistic features
• MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detection
• Attention-based Bidirectional LSTM for Deceptive Opinion Spam Classification

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