Corpus

By P. Krogh, I. Koskinen. 2018

Subfields: Evaluation & Benchmarks

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In Evaluation & Benchmarks

1. Deepika Nyavanandi
2. Simone A. Ludwig
3. Ahmed Hassan Awadallah
4. Saghar Hosseini
5. Hamid Palangi
6. Maggie Charles
7. Apeksha Shewalkar

Citations in the corpus

• An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models (2023, methodology): “Similarly, we pre-trained 23 student models with language modeling objective on OpenWeb-Text (Gokaslan et al., 2019) corpus for 1 epoch.”
• Towards Automated Circuit Discovery for Mechanistic Interpretability (2023, methodology): “Our induction experiments were performed on a 2-layer, 8-head-per-layer attention only transformer trained on OpenWebText (Gokaslan et al., 2019).”
• Performance Evaluation of Deep Neural Networks Applied to Speech Recognition: RNN, LSTM and GRU (2019, methodology): “We have used a subset of the improved TED-LIUM release 2 corpus [10].”
• The Routledge Handbook of Corpus Linguistics (2011, background): “Another interface which provides access to data from a number of corpora as well as corpus-based resources is corpus.byu.edu (Davies 2020).”
• Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors (2022, unknown): “Therefore, we finetune GPT2-XL on these data mixed with sentences from OpenWebText [10], a public version of GPT2’s training data.”