David Alvarez-Melis

90 papers A* 14A 7B 1Journal 61Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Critical Look at Targeted Instruction Selection: Disentangling What Matters (and What Doesn't). CoRR Nihal V. Nayak, Paula Rodriguez Diaz, Neha Hulkund, Sara Beery, David Alvarez-Melis
2026	J	`jnl`	Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions. CoRR Saleh Afroogh, Seyd Ishtiaque Ahmed, Petra Ahrweiler, David Alvarez-Melis, Mansur Maturidi Arief, Emilia Barakova, Falco J. Bargagli-Stoffi, Erdem Biyik, Hanjie Chen, Xiang 'Anthony' Chen, Robert Clements, Keeley Crockett, Amit Dhurandhar, Fethiye Irmak Dogan, Mollie Dollinger, Motahhare Eslami, Aldo A. Faisal, Arya Farahi, Melanie Fernandez Pradie, Saadia Gabrie, Diego Garcia-Olano, Marzyeh Ghassemi, Shaona Ghosh, Hatice Gunes, Ehsan Hajiramezanali, Stefan Haufe, Biwei Huang, Angel Hwang, Md Tauhidul Islam, Junfeng Jiao, Amir-Hossein Karimi, Saber Kazeminasab, Anastasia Kuzminykh, William G. La Cava, Brian Y. Lim, Xiaofeng Liu, Mohammad R. K. Mofrad, Alicia Parrish, María Pérez-Ortiz, Shriti Raj, Swabha Swayamdipta, Salmon Talebi, Kush R. Varshney, Mihaela Vorvoreanu, Lily Weng, Alice Xiang, Yiming Xu, Ding Zhao, Jieyu Zhao
2026	J	`jnl`	Reliable and Responsible Foundation Models: A Comprehensive Survey. CoRR Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2026	J	`jnl`	Stop Training for the Worst: Progressive Unmasking Accelerates Masked Diffusion Training. CoRR Jaeyeon Kim, Jonathan Geuter, David Alvarez-Melis, Sham M. Kakade, Sitan Chen
2025	J	`jnl`	Adam or Gauss-Newton? A Comparative Study In Terms of Basis Alignment and SGD Noise. CoRR Bingbin Liu, Rachit Bansal, Depen Morwani, Nikhil Vyas, David Alvarez-Melis, Sham M. Kakade
2025	J	`jnl`	Bispectral OT: Dataset Comparison using Symmetry-Aware Optimal Transport. CoRR Annabel Ma, Kaiying Hou, David Alvarez-Melis, Melanie Weber
2025	J	`jnl`	Boomerang Distillation Enables Zero-Shot Model Size Interpolation. CoRR Sara Kangaslahti, Nihal V. Nayak, Jonathan Geuter, Marco Fumero, Francesco Locatello, David Alvarez-Melis
2025	J	`jnl`	Can Interpretation Predict Behavior on Unseen Data? CoRR Victoria R. Li, Jenny Kaufmann, Martin Wattenberg, David Alvarez-Melis, Naomi Saphra
2025	J	`jnl`	Causal integration of chemical structures improves representations of microscopy images for morphological profiling. CoRR Yemin Yu, Neil A. Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex X. Lu
2025	J	`jnl`	Continuous Language Model Interpolation yields Dynamic and Controllable Text Generation. Trans. Mach. Learn. Res. Sara Kangaslahti, David Alvarez-Melis
2025	A	`conf`	DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows. AISTATS Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis
2025	J	`jnl`	DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows. CoRR Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis
2025	A*	`conf`	Data Drives Unstable Hierarchical Generalization in LMs. EMNLP Tian Qin, Naomi Saphra, David Alvarez-Melis
2025	J	`jnl`	Decomposing Elements of Problem Solving: What "Math" Does RL Teach? CoRR Tian Qin, Core Francisco Park, Mujin Kwun, Aaron Walsman, Eran Malach, Nikhil Anand, Hidenori Tanaka, David Alvarez-Melis
2025	J	`jnl`	Distributional Scaling Laws for Emergent Capabilities. CoRR Rosie Zhao, Tian Qin, David Alvarez-Melis, Sham M. Kakade, Naomi Saphra
2025	J	`jnl`	Guided Speculative Inference for Efficient Test-Time Alignment of LLMs. CoRR Jonathan Geuter, Youssef Mroueh, David Alvarez-Melis
2025	J	`jnl`	IGDA: Interactive Graph Discovery through Large Language Model Agents. CoRR Alex Havrilla, David Alvarez-Melis, Nicolò Fusi
2025	A*	`conf`	Investigating the interaction of linguistic and mathematical reasoning in language models using multilingual number puzzles. EMNLP Antara Raaghavi Bhattacharya, Isabel Papadimitriou, Kathryn Davidson, David Alvarez-Melis
2025	J	`jnl`	Investigating the interaction of linguistic and mathematical reasoning in language models using multilingual number puzzles. CoRR Antara Raaghavi Bhattacharya, Isabel Papadimitriou, Kathryn Davidson, David Alvarez-Melis
2025	—	`conf`	JONES-19: A Cultural Image Dataset Based on The Grammar of Ornament. KUI Linh Pham, Stuart M. Shieber, David Alvarez-Melis, Alexandros Haridis
2025	J	`jnl`	KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning. CoRR Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
2025	J	`jnl`	Let's (not) just put things in Context: Test-Time Training for Long-Context LLMs. CoRR Rachit Bansal, Aston Zhang, Rishabh Tiwari, Lovish Madaan, Sai Surya Duvvuri, Devvrit Khatri, David Brandfonbrener, David Alvarez-Melis, Prajjwal Bhargava, Mihir Sanjay Kale, Samy Jelassi
2025	A*	`conf`	Mixture of Parrots: Experts improve memorization more than reasoning. ICLR Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach
2025	J	`jnl`	Reliable and Responsible Foundation Models. Trans. Mach. Learn. Res. Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025	J	`jnl`	To Backtrack or Not to Backtrack: When Sequential Search Limits Model Reasoning. CoRR Tian Qin, David Alvarez-Melis, Samy Jelassi, Eran Malach
2025	A	`conf`	What is the Right Notion of Distance between Predict-then-Optimize Tasks? UAI Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe
2024	A*	`conf`	A Label is Worth A Thousand Images in Dataset Distillation. NeurIPS Tian Qin, Zhiwei Deng, David Alvarez-Melis
2024	J	`jnl`	A Label is Worth a Thousand Images in Dataset Distillation. CoRR Tian Qin, Zhiwei Deng, David Alvarez-Melis
2024	J	`jnl`	Adapting Language Models via Token Translation. CoRR Zhili Feng, Tanya Marwah, Nicolò Fusi, David Alvarez-Melis, Lester Mackey
2024	J	`jnl`	CharED: Character-wise Ensemble Decoding for Large Language Models. CoRR Kevin Gu, Eva Tuecke, Dmitriy Katz, Raya Horesh, David Alvarez-Melis, Mikhail Yurochkin
2024	J	`jnl`	Continuous Language Model Interpolation for Dynamic and Controllable Text Generation. CoRR Sara Kangaslahti, David Alvarez-Melis
2024	J	`jnl`	Distributional Dataset Distillation with Subtask Decomposition. CoRR Tian Qin, Zhiwei Deng, David Alvarez-Melis
2024	J	`jnl`	Mixture of Parrots: Experts improve memorization more than reasoning. CoRR Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach
2024	J	`jnl`	Sometimes I am a Tree: Data Drives Unstable Hierarchical Generalization. CoRR Tian Qin, Naomi Saphra, David Alvarez-Melis
2024	—	`conf`	Strongly Isomorphic Neural Optimal Transport Across Incomparable Spaces. GRaM Athina Sotiropoulou, David Alvarez-Melis
2024	J	`jnl`	Strongly Isomorphic Neural Optimal Transport Across Incomparable Spaces. CoRR Athina Sotiropoulou, David Alvarez-Melis
2024	A*	`conf`	Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. ICML Junhong Shen, Neil A. Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolò Fusi
2024	J	`jnl`	Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. CoRR Junhong Shen, Neil A. Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolò Fusi
2024	J	`jnl`	Understanding the Role of Functional Diversity in Weight-Ensembling with Ingredient Selection and Multidimensional Scaling. CoRR Alex Rojas, David Alvarez-Melis
2024	J	`jnl`	What is the Right Notion of Distance between Predict-then-Optimize Tasks? CoRR Paula Rodriguez Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe
2023	—	`conf`	Domain adaptation using optimal transport for invariant learning using histopathology datasets. MIDL Kianoush Falahkheirkhah, Alex Xijie Lu, David Alvarez-Melis, Grace Huynh
2023	J	`jnl`	Domain adaptation using optimal transport for invariant learning using histopathology datasets. CoRR Kianoush Falahkheirkhah, Alex Xijie Lu, David Alvarez-Melis, Grace Huynh
2023	A	`conf`	Generating Synthetic Datasets by Interpolating along Generalized Geodesics. UAI Jiaojiao Fan, David Alvarez-Melis
2023	J	`jnl`	Generating Synthetic Datasets by Interpolating along Generalized Geodesics. CoRR Jiaojiao Fan, David Alvarez-Melis
2023	A*	`conf`	InfoOT: Information Maximizing Optimal Transport. ICML Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
2022	A*	`conf`	Are GANs overkill for NLP? NeurIPS David Alvarez-Melis, Vikas Garg, Adam Kalai
2022	J	`jnl`	Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport. CoRR David Alvarez-Melis, Nicolò Fusi, Lester Mackey, Tal Wagner
2022	—	`conf`	Hierarchical Optimal Transport for Comparing Histopathology Datasets. MIDL Anna Yeaton, Rahul G. Krishnan, Rebecca J. Mieloszyk, David Alvarez-Melis, Grace Huynh
2022	J	`jnl`	Hierarchical Optimal Transport for Comparing Histopathology Datasets. CoRR Anna Yeaton, Rahul G. Krishnan, Rebecca J. Mieloszyk, David Alvarez-Melis, Grace Huynh
2022	J	`jnl`	InfoOT: Information Maximizing Optimal Transport. CoRR Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
2022	J	`jnl`	Interpretable Distribution Shift Detection using Optimal Transport. CoRR Neha Hulkund, Nicolò Fusi, Jennifer Wortman Vaughan, David Alvarez-Melis
2022	J	`jnl`	Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings. CoRR Frederike Lübeck, Charlotte Bunne, Gabriele Gut, Jacobo Sarabia del Castillo, Lucas Pelkmans, David Alvarez-Melis
2022	J	`jnl`	Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks. Trans. Mach. Learn. Res. David Alvarez-Melis, Yair Schiff, Youssef Mroueh
2022	J	`jnl`	Transfer RL via the Undo Maps Formalism. CoRR Abhi Gupta, Ted Moskovitz, David Alvarez-Melis, Aldo Pacchiano
2022	J	`jnl`	Why GANs are overkill for NLP. CoRR David Alvarez-Melis, Vikas Garg, Adam Tauman Kalai
2021	J	`jnl`	A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
2021	A*	`conf`	Dataset Dynamics via Gradient Flows in Probability Space. ICML David Alvarez-Melis, Nicolò Fusi
2021	B	`conf`	From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
2021	J	`jnl`	Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks. CoRR David Alvarez-Melis, Yair Schiff, Youssef Mroueh
2020	A*	`conf`	Geometric Dataset Distances via Optimal Transport. NeurIPS David Alvarez-Melis, Nicolò Fusi
2020	J	`jnl`	Geometric Dataset Distances via Optimal Transport. CoRR David Alvarez-Melis, Nicoló Fusi
2020	J	`jnl`	Gradient Flows in Dataset Space. CoRR David Alvarez-Melis, Nicolò Fusi
2020	A	`conf`	Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces. AISTATS David Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola
2019	A*	`conf`	Functional Transparency for Structured Data: a Game-Theoretic Approach. ICML Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola
2019	J	`jnl`	Functional Transparency for Structured Data: a Game-Theoretic Approach. CoRR Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola
2019	A*	`conf`	Learning Generative Models across Incomparable Spaces. ICML Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka
2019	J	`jnl`	Learning Generative Models across Incomparable Spaces. CoRR Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka
2019	J	`jnl`	Probabilistic Bias Mitigation in Word Embeddings. CoRR Hailey James-Sorenson, David Alvarez-Melis
2019	A	`conf`	Towards Optimal Transport with Global Invariances. AISTATS David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola
2019	—	`conf`	Towards Robust, Locally Linear Deep Networks. ICLR (Poster) Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola
2019	J	`jnl`	Towards Robust, Locally Linear Deep Networks. CoRR Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola
2019	J	`jnl`	Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces. CoRR David Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola
2019	J	`jnl`	Weight of Evidence as a Basis for Human-Oriented Explanations. CoRR David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach
2018	—	`conf`	Distributional Adversarial Networks. ICLR (Workshop) Chengtao Li, David Alvarez-Melis, Keyulu Xu, Stefanie Jegelka, Suvrit Sra
2018	J	`jnl`	Game-Theoretic Interpretability for Temporal Modeling. CoRR Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola
2018	A*	`conf`	Gromov-Wasserstein Alignment of Word Embedding Spaces. EMNLP David Alvarez-Melis, Tommi S. Jaakkola
2018	J	`jnl`	Gromov-Wasserstein Alignment of Word Embedding Spaces. CoRR David Alvarez-Melis, Tommi S. Jaakkola
2018	J	`jnl`	On the Robustness of Interpretability Methods. CoRR David Alvarez-Melis, Tommi S. Jaakkola
2018	A	`conf`	Structured Optimal Transport. AISTATS David Alvarez-Melis, Tommi S. Jaakkola, Stefanie Jegelka
2018	J	`jnl`	Towards Optimal Transport with Global Invariances. CoRR David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola
2018	A*	`conf`	Towards Robust Interpretability with Self-Explaining Neural Networks. NeurIPS David Alvarez-Melis, Tommi S. Jaakkola
2018	J	`jnl`	Towards Robust Interpretability with Self-Explaining Neural Networks. CoRR David Alvarez-Melis, Tommi S. Jaakkola
2017	A*	`conf`	A causal framework for explaining the predictions of black-box sequence-to-sequence models. EMNLP David Alvarez-Melis, Tommi S. Jaakkola
2017	J	`jnl`	A causal framework for explaining the predictions of black-box sequence-to-sequence models. CoRR David Alvarez-Melis, Tommi S. Jaakkola
2017	J	`jnl`	Distributional Adversarial Networks. CoRR Chengtao Li, David Alvarez-Melis, Keyulu Xu, Stefanie Jegelka, Suvrit Sra
2017	J	`jnl`	Structured Optimal Transport. CoRR David Alvarez-Melis, Tommi S. Jaakkola, Stefanie Jegelka
2017	—	`conf`	Tree-structured decoding with doubly-recurrent neural networks. ICLR (Poster) David Alvarez-Melis, Tommi S. Jaakkola
2016	A	`conf`	Topic Modeling in Twitter: Aggregating Tweets by Conversations. ICWSM David Alvarez-Melis, Martin Saveski
2016	J	`jnl`	Word Embeddings as Metric Recovery in Semantic Spaces. Trans. Assoc. Comput. Linguistics Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola
2015	J	`jnl`	Word, graph and manifold embedding from Markov processes. CoRR Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola