Papers by Adrian Popescu
MAD-TSC: A Multilingual Aligned News Dataset for Target-dependent Sentiment Classification (2023.acl-long)
Copied to clipboard
| Challenge: | Sentiment classification is a task that requires domain-specific datasets. |
| Approach: | They propose a new dataset which includes aligned examples in eight languages . they show that machine translations can replace manual ones and that results match English . |
| Outcome: | The proposed dataset compares the performance of the proposed model with existing datasets in eight languages and human and machine translations. |
Analyzing Political Bias in LLMs via Target-Oriented Sentiment Classification (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing methods to analyze political biases rely on small-size intermediate tasks and the LLMs themselves. |
| Approach: | They propose an entropy-based inconsistency metric to encode political biases . they insert 1319 demographically and politically diverse politician names in 450 political sentences . |
| Outcome: | The proposed method combines high accuracy with a correct understanding of the candidate candidate. |
A Scalable Entity-Based Framework for Auditing Bias in Large Language Models (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing approaches to bias evaluation in large language models trade ecological validity for statistical control, or use artificial prompts that lack scale and rigor. |
| Approach: | They propose a framework that uses named entities as probes to measure bias in large language models. |
| Outcome: | The proposed framework reproduces bias patterns observed in natural text, enabling large-scale analysis. |