2 citations · 3 across the 6 of their papers we have counts for
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A MISMATCHED Benchmark for Scientific Natural Language Inference
Firoz Shaik, Mobashir Sadat, Nikita Gautam +2
Scientific Natural Language Inference (NLI) is the task of predicting the semantic relation between a pair of sentences extracted from research articles. Existing datasets for this…
Co-training for Low Resource Scientific Natural Language Inference
Mobashir Sadat, Cornelia Caragea
Scientific Natural Language Inference (NLI) is the task of predicting the semantic relation between a pair of sentences extracted from research articles. The automatic annotation m…
MSciNLI: A Diverse Benchmark for Scientific Natural Language Inference
Mobashir Sadat, Cornelia Caragea
The task of scientific Natural Language Inference (NLI) involves predicting the semantic relation between two sentences extracted from research articles. This task was recently pro…
DelucionQA: Detecting Hallucinations in Domain-specific Question Answering
Mobashir Sadat, Zhengyu Zhou, Lukas Lange +6
Hallucination is a well-known phenomenon in text generated by large language models (LLMs). The existence of hallucinatory responses is found in almost all application scenarios e.…
Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference
Mobashir Sadat, Cornelia Caragea
Natural Language Inference (NLI) or Recognizing Textual Entailment (RTE) aims at predicting the relation between a pair of sentences (premise and hypothesis) as entailment, contrad…
Hierarchical Multi-Label Classification of Scientific Documents
Mobashir Sadat, Cornelia Caragea
Automatic topic classification has been studied extensively to assist managing and indexing scientific documents in a digital collection. With the large number of topics being avai…