Nazli Goharian
Artificial Intelligence · 2013–2021
A researcher in the Science corpus: 14 papers; trusts 263 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 214 citations into it; #5,659 of 35,345 by trust here, #4,829 by citations
- Natural Language Processing — 128 citations into it; #1,471 of 5,688 by trust here, #1,391 by citations
- Information Retrieval & Search — 71 citations into it; #213 of 1,022 by trust here, #300 by citations
- Information Systems — 63 citations into it; #8,544 of 8,771 by trust here, #3,012 by citations
- Computer Vision and Pattern Recognition — 48 citations into it
- Large Language Models — 34 citations into it
- Evaluation & Benchmarks — 20 citations into it
- Model Architectures — 18 citations into it
Whom Nazli Goharian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Jacob Devlin
- Ilya Sutskever
- Jimmy Ba
- Alex Krizhevsky
- Kyunghyun Cho
- Yann LeCun
- Alex Graves
Who trusts Nazli Goharian overall
- Sean MacAvaney
- Jimmy J. Lin
- Sebastian Hofstätter
- Rodrigo Nogueira
- Zeynep Akkalyoncu Yilmaz
- Arman Cohan
- Abeed Sarker
- Andrew Yates
- Sajad Sotudeh
- Luca Soldaini
Papers from Nazli Goharian's perspective
Ordered by how strongly the researchers Nazli Goharian trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents (2018) — 950 citations
- On Generating Extended Summaries of Long Documents (2020) — 19 citations
- GUIR @ LongSumm 2020: Learning to Generate Long Summaries from Scientific Documents (2020) — 11 citations
- Depression and Self-Harm Risk Assessment in Online Forums (2017) — 350 citations
- CEDR: Contextualized Embeddings for Document Ranking (2019) — 371 citations
- SLEDGE: A Simple Yet Effective Baseline for Coronavirus Scientific Knowledge Search (2020) — 23 citations
- ADRTrace: Detecting Expected and Unexpected Adverse Drug Reactions from User Reviews on Social Media Sites (2013) — 104 citations
- Efficient Document Re-Ranking for Transformers by Precomputing Term Representations (2020) — 132 citations
- ToxCCIn: Toxic Content Classification with Interpretability (2021) — 20 citations
- Expansion via Prediction of Importance with Contextualization (2020) — 122 citations
- Training Curricula for Open Domain Answer Re-Ranking (2020) — 20 citations
- Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-Shot Learning (2019) — 31 citations
- Hate speech detection: Challenges and solutions (2019) — 568 citations
- Effects of Sampling on Twitter Trend Detection (2016) — 7 citations