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20182025
most citedEnd-to-End Self-Debiasing Framework for Robust NLU Training

29 citations · 65 across the 13 of their papers we have counts for

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15 papers · 1 filter

cs.CL2025

Integral Transformer: Denoising Attention, Not Too Much Not Too Little

Ivan Kobyzev, Abbas Ghaddar, Dingtao Hu +1

Softmax self-attention often assigns disproportionate weight to semantically uninformative tokens such as special tokens and punctuation, a phenomenon known as attention noise. Whi…

cs.CL2024

EWEK-QA: Enhanced Web and Efficient Knowledge Graph Retrieval for Citation-based Question Answering Systems

Mohammad Dehghan, Mohammad Ali Alomrani, Sunyam Bagga +12

The emerging citation-based QA systems are gaining more attention especially in generative AI search applications. The importance of extracted knowledge provided to these systems i…

cs.CL2024

OTTAWA: Optimal TransporT Adaptive Word Aligner for Hallucination and Omission Translation Errors Detection

Chenyang Huang, Abbas Ghaddar, Ivan Kobyzev +3

Recently, there has been considerable attention on detecting hallucinations and omissions in Machine Translation (MT) systems. The two dominant approaches to tackle this task invol…

cs.CL2024

CHARP: Conversation History AwaReness Probing for Knowledge-grounded Dialogue Systems

Abbas Ghaddar, David Alfonso-Hermelo, Philippe Langlais +3

In this work, we dive deep into one of the popular knowledge-grounded dialogue benchmarks that focus on faithfulness, FaithDial. We show that a significant portion of the FaithDial…

cs.CL2024

On the importance of Data Scale in Pretraining Arabic Language Models

Abbas Ghaddar, Philippe Langlais, Mehdi Rezagholizadeh +1

Pretraining monolingual language models have been proven to be vital for performance in Arabic Natural Language Processing (NLP) tasks. In this paper, we conduct a comprehensive st…

cs.CL2023

AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing

Asaad Alghamdi, Xinyu Duan, Wei Jiang +9

Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we pr…