11 citations · 20 across the 11 of their papers we have counts for
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Layer or Representation Space: What makes BERT-based Evaluation Metrics Robust?
Doan Nam Long Vu, Nafise Sadat Moosavi, Steffen Eger
The evaluation of recent embedding-based evaluation metrics for text generation is primarily based on measuring their correlation with human evaluations on standard benchmarks. How…
Scoring Coreference Chains with Split-Antecedent Anaphors
Silviu Paun, Juntao Yu, Nafise Sadat Moosavi +1
Anaphoric reference is an aspect of language interpretation covering a variety of types of interpretation beyond the simple case of identity reference to entities introduced via no…
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization
Prasetya Ajie Utama, Joshua Bambrick, Nafise Sadat Moosavi +1
Neural abstractive summarization models are prone to generate summaries which are factually inconsistent with their source documents. Previous work has introduced the task of recog…
Adaptable Adapters
Nafise Sadat Moosavi, Quentin Delfosse, Kristian Kersting +1
State-of-the-art pretrained NLP models contain a hundred million to trillion parameters. Adapters provide a parameter-efficient alternative for the full finetuning in which we can…
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Prasetya Ajie Utama, Nafise Sadat Moosavi, Victor Sanh +1
Recent prompt-based approaches allow pretrained language models to achieve strong performances on few-shot finetuning by reformulating downstream tasks as a language modeling probl…
Learning to Reason for Text Generation from Scientific Tables
Nafise Sadat Moosavi, Andreas Rücklé, Dan Roth +1
In this paper, we introduce SciGen, a new challenge dataset for the task of reasoning-aware data-to-text generation consisting of tables from scientific articles and their correspo…