Vivek Srikumar

Artificial Intelligence · 2008–2026

A researcher in the Science corpus: 18 papers; trusts 426 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 437 citations into it; #9,861 of 35,345 by trust here, #7,346 by citations
• Natural Language Processing — 266 citations into it; #2,063 of 5,688 by trust here, #2,156 by citations
• Computer Vision and Pattern Recognition — 138 citations into it
• Evaluation & Benchmarks — 71 citations into it
• Representation & Self-Supervised Learning — 64 citations into it
• Safety, Robustness & Interpretability — 62 citations into it; #877 of 2,251 by trust here, #984 by citations
• Large Language Models — 59 citations into it
• Information Systems — 53 citations into it

Whom Vivek Srikumar trusts overall

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

1. Michael Collins
2. Dan Roth
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Ilya Sutskever
7. Alex Krizhevsky
8. Sepp Hochreiter
9. Jimmy Ba
10. Yann LeCun

Who trusts Vivek Srikumar overall

1. Daniel Khashabi
2. Peter Clark
3. Tushar Khot
4. Ashish Sabharwal
5. Rik Koncel-Kedziorski
6. Sunipa Dev
7. Oren Etzioni
8. Hannaneh Hajishirzi
9. Dan Roth
10. Oyvind Tafjord

Papers from Vivek Srikumar's perspective

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

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

Their papers

• On Measuring and Mitigating Biased Inferences of Word Embeddings (2019) — 198 citations
• Modeling Biological Processes for Reading Comprehension (2014) — 240 citations
• A Logic-Driven Framework for Consistency of Neural Models (2019) — 120 citations
• OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings (2020) — 60 citations
• ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars (2016) — 1,990 citations
• Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks (2018) — 676 citations
• LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum (2026)
• A Survey of Model Architectures in Information Retrieval (2025)
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
• Right for the Right Reason: Evidence Extraction for Trustworthy Tabular Reasoning (2022) — 18 citations
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
• DirectProbe: Studying Representations without Classifiers (2021) — 38 citations
• UNQOVERing Stereotypical Biases via Underspecified Questions (2020) — 167 citations
• CogCompNLP: Your Swiss Army Knife for NLP (2018) — 29 citations
• DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning (2017) — 1,955 citations
• A Joint Model for Extended Semantic Role Labeling (2011) — 50 citations
• Discriminative Learning over Constrained Latent Representations (2010) — 83 citations
• Importance of Semantic Representation: Dataless Classification (2008) — 337 citations