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Oana Cocarascu

19 papers · 2017–2026 · 7 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (8) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (42)
🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (8) πŸ’Ž Century Club (18) ❓ The Questioner πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (5) πŸ—ƒοΈ Keyword Collector (74)

Conferences

EMNLP (10) ACL (2) EACL (2) NAACL (2) AAAI (1) COLING (1) IJCAI (1)

Papers

Improving Dialect Robustness in Large Language Models via LoRA and Mixture-of-Experts EACL 2026 FactEval: Evaluating the Robustness of Fact Verification Systems in the Era of Large Language Models NAACL 2025 I-GUARD: Interpretability-Guided Parameter Optimization for Adversarial Defense EMNLP 2025 Can Large Language Models Understand Argument Schemes? ACL 2025 Identifying Reasons for Bias: An Argumentation-Based Approach AAAI 2024 ChartCheck: Explainable Fact-Checking over Real-World Chart Images ACL 2024 The Automated Verification of Textual Claims (AVeriTeC) Shared Task EMNLP 2024 Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking EACL 2023 Multimodal Automated Fact-Checking: A Survey EMNLP 2023 Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data EMNLP 2023 A Robustness Evaluation Framework for Argument Mining COLING 2022 PubHealthTab: A Public Health Table-based Dataset for Evidence-based Fact Checking NAACL 2022 The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task EMNLP 2021 Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER) EMNLP 2019 The FEVER2.0 Shared Task EMNLP 2019 Proceedings of the First Workshop on Fact Extraction and VERification (FEVER) EMNLP 2018 Argumentation-Based Recommendations: Fantastic Explanations and How to Find Them IJCAI 2018 The Fact Extraction and VERification (FEVER) Shared Task EMNLP 2018 Identifying attack and support argumentative relations using deep learning EMNLP 2017