Author

Rico Angell

Observed name: Angell, Rico

Institution: New York University

Observed institutions: Google (United States), University of Massachusetts Amherst, University of Michigan, New York University

ORCID: 0009-0009-1699-0735

Observed ORCID: 0009-0009-1699-0735

OpenAlex ID: A5047594082

Themis: automatically testing software for discrimination

2018 · Rico Angell, Brittany Johnson, et al. · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · 94

Clustering-based Inference for Biomedical Entity Linking

2021 · Rico Angell, Nicholas Monath, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 52

Entity Linking via Explicit Mention-Mention Coreference Modeling

2022 · Dhruv Agarwal, Rico Angell, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 20

Don’t Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization

2017 · Rico Angell, Grant Schoenebeck · Lecture notes in computer science · 15

Low resource recognition and linking of biomedical concepts from a large ontology

2021 · Sunil Mohan, Rico Angell, et al. · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · 13

Relation Matters in Sampling: A Scalable Multi-Relational Graph Neural Network for Drug-Drug Interaction Prediction

2021 · Feeney, Arthur, Gupta, Rishabh, et al. · arXiv (Cornell University) · 8

Fairkit, fairkit, on the wall, who’s the fairest of them all? Supporting fairness-related decision-making

2023 · Brittany Johnson, Jesse Bartola, et al. · EURO Journal on Decision Processes · 7

Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models

2020 · Johnson, Brittany, Bartola, Jesse, et al. · arXiv (Cornell University) · 7

Entity Linking and Discovery via Arborescence-based Supervised Clustering

2021 · Agarwal, Dhruv, Angell, Rico, et al. · arXiv (Cornell University) · 6

Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization

2022 · Nishant Yadav, Nicholas Monath, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 5

A Topological Approach to Hardware Bug Triage

2015 · Rico Angell, Ben Oztalay, et al. · International Workshop on Microprocessor Test and Verification (MTV) · 5

Event and Entity Coreference using Trees to Encode Uncertainty in Joint Decisions

2021 · Nishant Yadav, Nicholas Monath, et al. · Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC) · 4

Inferring Latent Velocities from Weather Radar Data using Gaussian Processes

2018 · Rico Angell, Daniel Sheldon · neural information processing systems · 3

Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization

2016 · Angell, Rico, Schoenebeck, Grant · arXiv (Cornell University) · 3

Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models

2024 · Adam Karvonen, Benjamin Wright, et al. · neural information processing systems · 1

Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching

2023 · Angell, Rico, McCallum, Andrew · arXiv (Cornell University) · 1

Clustering-based Inference for Zero-Shot Biomedical Entity Linking.

2020 · Rico Angell, Nicholas Monath, et al. · arXiv (Cornell University) · 1

BOReFT: Manifold Steering of Language Models for Black-box Optimization

2026 · Agarwal, Dhruv, Angell, Rico, et al. · arXiv (Cornell University)

AURA-Eval: Evaluation Framework for Acting Under Risk Awareness in LLM Agent Trajectories

2026 · Shang, Ruoxi, Androna, Christina-Maria, et al. · arXiv (Cornell University)

Mitigating Adaptive Attacks against Reasoning Models with Activation Consistency Training

2026 · Shah, Avidan, Brinkmann, Jannik, et al. · arXiv (Cornell University)

On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation

2026 · Han, Andy, Fujimoto, Kristina, et al. · arXiv (Cornell University)

Estimating Tail Risks in Language Model Output Distributions

2026 · Angell, Rico, Singhal, Raghav, et al. · arXiv (Cornell University)

Is It Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort

2025 · Wang, Xinpeng, Joshi, Nitish, et al. · arXiv (Cornell University)

Jailbreak Transferability Emerges from Shared Representations

2025 · Angell, Rico, Brinkmann, Jannik, et al. · arXiv (Cornell University)

Monitoring Decomposition Attacks in LLMs with Lightweight Sequential Monitors

2025 · Yueh-Han, Chen, Joshi, Nitish, et al. · arXiv (Cornell University)

Works count: 32

Citation count: 245

H-index: 7

I10-index: 5