Papers by Abir Harrasse
TinySQL: A Progressive Text-to-SQL Dataset for Mechanistic Interpretability Research (2025.emnlp-main)
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| Challenge: | Existing text-to-SQL datasets are too complex and noisy for rigorous interpretability analysis. |
| Approach: | They propose text-to-SQL generation as an ideal task to study mechanistic interpretability . they use edge attribution patching and sparse autoencoders to identify minimal circuits . |
| Outcome: | The proposed task combines the formal structure of toy tasks with real-world complexity. |
Debate, Deliberate, Decide (D3): A Cost-Aware Adversarial Framework for Reliable and Interpretable LLM Evaluation (2026.eacl-long)
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| Challenge: | Existing evaluation tools for Large Language Models (LLMs) are inconsistency, bias, and lack of transparent decision criteria. |
| Approach: | They propose a cost-aware, adversarial multi-agent framework that orchestrates structured debate among role-specialized agents to produce reliable and interpretable evaluations. |
| Outcome: | The proposed framework orchestrates structured debate among role-specialized agents to produce reliable and interpretable evaluations. |