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cs.CL2026★ 1 cited
Reason and Verify: A Framework for Faithful Retrieval-Augmented Generation
Eeham Khan, Luis Rodriguez, Marc Queudot
Retrieval-Augmented Generation (RAG) significantly improves the factuality of Large Language Models (LLMs), yet standard pipelines often lack mechanisms to verify inter- mediate re…
cs.CL2026
Low-Resource Dialect Adaptation of Large Language Models: A French Dialect Case-Study
Eeham Khan, Firas Saidani, Owen Van Esbroeck +2
Despite the widespread adoption of Large Language Models (LLMs), their strongest capabilities remain largely confined to a small number of high-resource languages for which there i…
cs.CL2025
CLaC at SemEval-2025 Task 6: A Multi-Architecture Approach for Corporate Environmental Promise Verification
Nawar Turk, Eeham Khan, Leila Kosseim
This paper presents our approach to the SemEval-2025 Task~6 (PromiseEval), which focuses on verifying promises in corporate ESG (Environmental, Social, and Governance) reports. We…