A Topological Approach to Hardware Bug Triage. - Rico Angell; Ben Oztalay; Andrew DeOrio (MTV, 2015)

Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization. - Rico Angell; Grant Schoenebeck (WINE, 2017)

Inferring Latent Velocities from Weather Radar Data using Gaussian Processes. - Rico Angell; Daniel Sheldon (NeurIPS, 2018)

Themis: automatically testing software for discrimination. - Rico Angell; Brittany Johnson; Yuriy Brun; Alexandra Meliou (ESEC/SIGSOFT FSE, 2018)

Clustering-based Inference for Zero-Shot Biomedical Entity Linking. - Rico Angell; Nicholas Monath; Sunil Mohan; Nishant Yadav; Andrew McCallum (CoRR, 2020)

Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models. - Brittany Johnson; Jesse Bartola; Rico Angell; Katherine A. Keith; Sam Witty; Stephen J. Giguere; Yuriy Brun (CoRR, 2020)

Low resource recognition and linking of biomedical concepts from a large ontology. - Sunil Mohan; Rico Angell; Nicholas Monath; Andrew McCallum (BCB, 2021)

Clustering-based Inference for Biomedical Entity Linking. - Rico Angell; Nicholas Monath; Sunil Mohan; Nishant Yadav; Andrew McCallum (NAACL-HLT, 2021)

Relation Matters in Sampling: A Scalable Multi-Relational Graph Neural Network for Drug-Drug Interaction Prediction. - Arthur Feeney; Rishabh Gupta; Veronika Thost; Rico Angell; Gayathri Chandu; Yash Adhikari; Tengfei Ma 001 (CoRR, 2021)

Entity Linking and Discovery via Arborescence-based Supervised Clustering. - Dhruv Agarwal 003; Rico Angell; Nicholas Monath; Andrew McCallum (CoRR, 2021)

Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. - Nishant Yadav; Nicholas Monath; Rico Angell; Manzil Zaheer; Andrew McCallum (EMNLP, 2022)

Interactive Correlation Clustering with Existential Cluster Constraints. - Rico Angell; Nicholas Monath; Nishant Yadav; Andrew McCallum (ICML, 2022)

Entity Linking via Explicit Mention-Mention Coreference Modeling. - Dhruv Agarwal 003; Rico Angell; Nicholas Monath; Andrew McCallum (NAACL-HLT, 2022)

Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching. - Rico Angell; Andrew McCallum (ICML, 2024)

Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models. - Adam Karvonen; Benjamin Wright; Can Rager; Rico Angell; Jannik Brinkmann; Logan Smith; Claudio Mayrink Verdun; David Bau; Samuel Marks (NeurIPS, 2024)

Polynomial Precision Dependence Solutions to Alignment Research Center Matrix Completion Problems. - Rico Angell (CoRR, 2024)

Monitoring Decomposition Attacks in LLMs with Lightweight Sequential Monitors. - Chen Yueh-Han; Nitish Joshi; Yulin Chen; Maksym Andriushchenko; Rico Angell; He He 001 (CoRR, 2025)

Jailbreak Strength and Model Similarity Predict Transferability. - Rico Angell; Jannik Brinkmann; He He (CoRR, 2025)