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Argument Mining (AM) is a critical NLP task that remains significantly under-resourced in Arabic. This paper presents $\testtt{STAR-Ar}$, a BERT-BiLSTM-CRF architecture for argument discourse detection and classification, as our system for Daleel 2026, the inaugural Arabic argument mining shared task. The task requires...
This study examines whether individual text corpora from search histories can be used to simulate individual knowledge, and compared several large language models on this task, of which only Qwen3-1.7B proved viable.
This work introduces $\texttt{CLASP-Ar}$, which reformulates the Arabic-language stance detection task as cloze-style masked language modeling, and reformulates the task as cloze-style masked language modeling.
While TTLab's system localizes error spans effectively, classification of rare error types remains challenging, highlighting the need for data augmentation for tail categories.
We approach a cognitive simulation perspective on episodic and semantic memory in multiple-choice question answering by incorporating text from individual text corpora (ITC) into retrieval-augmented generation and DoRA fine-tuning. We web-crawl the search histories of 515 participants who answered 36 multiple-choice kn...
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