01이 칸의 논문
- SUVA: A Probabilistic Framework for Auditing LLMs with an Application to Social Preferences
- Learning from Earnings Calls: Graph-Based Conversational Modeling for Financial Prediction
- From Lexicons to Large Language Models: A Holistic Evaluation of Psychometric Text Analysis in Social Science Research
- Predicting Consumer In-Store Purchase Through Real-Time Video Analytics: An Advanced Computer Vision and Deep Learning Approach
- Generative AI as an Information Intermediary: A Novel Deep Learning Method for Financial Distress Prediction
- Predicting Instructor Performance in Online Education: An Interpretable Hierarchical Transformer with Contextual Attention
- Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model
- Quality Control for Crowd Workers and for Language Models: A Framework for Free-Text Response Evaluation with No Ground Truth
- Symptoms and Their Temporal Distributions: An Interpretable AI Approach for Depression Detection in Social Media
- KETCH: A Knowledge-Enhanced Transformer-Based Approach to Suicidal Ideation Detection from Social Media Content
- Guided Diverse Concept Miner (GDCM): Uncovering Relevant Constructs for Managerial Insights from Text
- TM-OKC: An Unsupervised Topic Model for Text in Online Knowledge Communities
- Unifying Algorithmic and Theoretical Perspectives: Emotions in Online Reviews and Sales
- A Theory-Driven Deep Learning Method for Voice Chat–Based Customer Response Prediction
- Extracting Actionable Insights from Text Data: A Stable Topic Model Approach
- Moving Emergency Response Forward: Leveraging Machine-Learning Classification of Disaster-Related Images Posted on Social Media
- Ontology-Based Information Extraction for Labeling Radical Online Content Using Distant Supervision
- Getting Personal: A Deep Learning Artifact for Text-Based Measurement of Personality
- Cross-Lingual Cybersecurity Analytics in the International Dark Web with Adversarial Deep Representation Learning
- sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics
- Understanding Medication Nonadherence from Social Media: A Sentiment-Enriched Deep Learning Approach
- Discovering Emerging Threats in the Hacker Community: A Nonparametric Emerging Topic Detection Framework
- Know Thy Context: Parsing Contextual Information from User Reviews for Recommendation Purposes
- Unveiling the Hidden Truth of Drug Addiction: A Social Media Approach Using Similarity Network-Based Deep Learning
- Mining Bilateral Reviews for Online Transaction Prediction: A Relational Topic Modeling Approach
- Enhancing Social Media Analysis with Visual Data Analytics: A Deep Learning Approach
- Semi-Supervised Cyber Threat Identification in Dark Net Markets: A Transductive and Deep Learning Approach
- A Comprehensive Analysis of Triggers and Risk Factors for Asthma Based on Machine Learning and Large Heterogeneous Data Sources
- A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections
- Leveraging Financial Social Media Data for Corporate Fraud Detection
02같은 주제, 다른 방법
- Leveraging Multiview Data Through Discrete and Regularized Deep Learning for Dynamic Financial Risk Prediction
- Forget Me If You Can: Auditing User Data Revocation in Recommendation Systems
- Align Generative Artificial Intelligence with Human Preferences: A Novel Large Language Model Fine-Tuning Method for Online Review Management
- Interpretable Recommendations and Parameter-Grounded LLM Explanations with Multigraph Attention
- Protecting the Linked Artificial Intelligence Repositories on Open Source Software Platforms: A Graph Self-Supervised Learning Approach
- Post-Earnings-Announcement Drift Prediction: Leveraging Postevent Investor Responses with Multitask Learning
- Automating in High-Expertise, Low-Label Environments: Evidence-Based Medicine by Expert-Augmented Few-Shot Learning
- Different but the Same? An Event-Driven Approach to Determine Probabilities of Data Duplication
- A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships
- Mitigating Bias in Hate Speech Detection With a Small Number of Expert Annotations: A Prompt-Based Learning Approach