| 2025 | AISTATS | DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows. | Jonathan Geuter, Clment Bonet, Anna Korba, David Alvarez-Melis |
| 2025 | EMNLP | Investigating the interaction of linguistic and mathematical reasoning in language models using multilingual number puzzles. | Antara Raaghavi Bhattacharya, Isabel Papadimitriou, Kathryn Davidson, David Alvarez-Melis |
| 2025 | EMNLP | Data Drives Unstable Hierarchical Generalization in LMs. | Tian Qin, Naomi Saphra, David Alvarez-Melis |
| 2025 | ICLR | Mixture of Parrots: Experts improve memorization more than reasoning. | Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach |
| 2025 | UAI | What is the Right Notion of Distance between Predict-then-Optimize Tasks? | Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe |
| 2024 | ICML | Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. | Junhong Shen, Neil A. Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicol Fusi |
| 2023 | ICML | InfoOT: Information Maximizing Optimal Transport. | Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis |
| 2023 | UAI | Generating Synthetic Datasets by Interpolating along Generalized Geodesics. | Jiaojiao Fan, David Alvarez-Melis |
| 2021 | HCOMP | From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. | David Alvarez-Melis, Harmanpreet Kaur, Hal Daum III, Hanna M. Wallach, Jennifer Wortman Vaughan |
| 2021 | ICML | Dataset Dynamics via Gradient Flows in Probability Space. | David Alvarez-Melis, Nicol Fusi |
| 2020 | AISTATS | Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces. | David Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola |
| 2019 | AISTATS | Towards Optimal Transport with Global Invariances. | David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola |
| 2019 | ICLR | Towards Robust, Locally Linear Deep Networks. | Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola |
| 2019 | ICML | Learning Generative Models across Incomparable Spaces. | Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka |
| 2019 | ICML | Functional Transparency for Structured Data: a Game-Theoretic Approach. | Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola |
| 2018 | AISTATS | Structured Optimal Transport. | David Alvarez-Melis, Tommi S. Jaakkola, Stefanie Jegelka |
| 2018 | EMNLP | Gromov-Wasserstein Alignment of Word Embedding Spaces. | David Alvarez-Melis, Tommi S. Jaakkola |
| 2018 | ICLR | Distributional Adversarial Networks. | Chengtao Li, David Alvarez-Melis, Keyulu Xu, Stefanie Jegelka, Suvrit Sra |
| 2017 | EMNLP | A causal framework for explaining the predictions of black-box sequence-to-sequence models. | David Alvarez-Melis, Tommi S. Jaakkola |
| 2017 | ICLR | Tree-structured decoding with doubly-recurrent neural networks. | David Alvarez-Melis, Tommi S. Jaakkola |
| 2016 | ICWSM | Topic Modeling in Twitter: Aggregating Tweets by Conversations. | David Alvarez-Melis, Martin Saveski |