Miruna Clinciu

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 7 papers; trusts 63 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 421 citations into it; #27,870 of 35,345 by trust here, #8,706 by citations
• Natural Language Processing — 313 citations into it; #4,576 of 5,688 by trust here, #1,487 by citations
• Evaluation & Benchmarks — 157 citations into it; #2,450 of 3,147 by trust here, #1,013 by citations
• Large Language Models — 88 citations into it
• Information Systems — 36 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• General Social Sciences — 13 citations into it
• Molecular Biology — 10 citations into it

Whom Miruna Clinciu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Anya Belz
2. Tomas Mikolov
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Yoon Kim
6. Diederik P. Kingma
7. Jacob Devlin
8. Ilya Sutskever
9. Alex Krizhevsky
10. Jekaterina Novikova

Who trusts Miruna Clinciu overall

1. Sarah Wiegreffe
2. Fan Huang
3. Swarnadeep Saha
4. Haewoon Kwak
5. Peter Hase
6. Sebastian Gehrmann
7. Jack Hessel

Papers from Miruna Clinciu's perspective

Ordered by how strongly the researchers Miruna Clinciu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics (2021) — 329 citations
• A Study of Automatic Metrics for the Evaluation of Natural Language Explanations (2021) — 62 citations
• Underreporting of errors in NLG output, and what to do about it (2021) — 42 citations
• Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definitions (2020) — 263 citations
• You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings (2022)
• Emergent Structures and Training Dynamics in Large Language Models (2022)
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations