Prithviraj Ammanabrolu

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 14 papers; trusts 482 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 369 citations into it; #5,157 of 35,345 by trust here, #4,747 by citations
• Natural Language Processing — 242 citations into it; #1,615 of 5,688 by trust here, #1,432 by citations
• Reinforcement Learning — 150 citations into it; #730 of 2,242 by trust here, #916 by citations
• Computer Vision and Pattern Recognition — 123 citations into it; #5,307 of 21,575 by trust here, #7,249 by citations
• Large Language Models — 49 citations into it
• Evaluation & Benchmarks — 34 citations into it
• Safety, Robustness & Interpretability — 29 citations into it
• Alignment & RLHF — 23 citations into it

Whom Prithviraj Ammanabrolu trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Alex Graves
5. Diederik P. Kingma
6. Richard S. Sutton
7. Alex Krizhevsky
8. Matthew J. Hausknecht
9. Tomas Mikolov
10. Dzmitry Bahdanau

Who trusts Prithviraj Ammanabrolu overall

1. Shunyu Yao
2. Matthew J. Hausknecht
3. Xiaoxiao Guo
4. Dan Hendrycks
5. Amal Alabdulkarim
6. Mark O. Riedl
7. Ximing Lu
8. Rajkumar Ramamurthy
9. Liwei Jiang
10. Rohan Rao

Papers from Prithviraj Ammanabrolu's perspective

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

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

• Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning (2018) — 132 citations
• Quark: Controllable Text Generation with Reinforced Unlearning (2022) — 277 citations
• Interactive Fiction Games: A Colossal Adventure (2019) — 261 citations
• Is Reinforcement Learning (Not) for Natural Language Processing?: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization (2022) — 301 citations
• Graph Constrained Reinforcement Learning for Natural Language Action Spaces (2020) — 139 citations
• Event Representations for Automated Story Generation with Deep Neural Nets (2017) — 231 citations
• Fine-Grained Human Feedback Gives Better Rewards for Language Model Training (2023) — 481 citations
• Behavior Cloned Transformers are Neurosymbolic Reasoners (2022) — 14 citations
• Automated Storytelling via Causal, Commonsense Plot Ordering (2020) — 73 citations
• Aligning to Social Norms and Values in Interactive Narratives (2022) — 54 citations
• Toward Automated Quest Generation in Text-Adventure Games (2019) — 32 citations
• Situated Dialogue Learning through Procedural Environment Generation (2021) — 14 citations
• Do Embodied Agents Dream of Pixelated Sheep?: Embodied Decision Making using Language Guided World Modelling (2023) — 115 citations
• How to Motivate Your Dragon: Teaching Goal-Driven Agents to Speak and Act in Fantasy Worlds (2020) — 45 citations