Santiago Miret

59 papers A* 10A 1B 1Journal 41Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CrystalGym: A New Benchmark for Materials Discovery Using Reinforcement Learning. CoRR Prashant Govindarajan, Mathieu Reymond, Antoine Clavaud, Mariano Phielipp, Santiago Miret, Sarath Chandar
2025	J	`jnl`	Diverse LLMs or Diverse Question Interpretations? That is the Ensembling Question. CoRR Rafael Rosales, Santiago Miret
2025	J	`jnl`	Efficient Morphology-Aware Policy Transfer to New Embodiments. CoRR Michael Przystupa, Hongyao Tang, Martin Jägersand, Santiago Miret, Mariano Phielipp, Matthew E. Taylor, Glen Berseth
2025	J	`jnl`	Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials. CoRR Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Sajid Mannan, N. M. Anoop Krishnan
2025	J	`jnl`	Evaluating Universal Machine Learning Force Fields Against Experimental Measurements. CoRR Sajid Mannan, Vaibhav Bihani, Carmelo Gonzales, Kin Long Kelvin Lee, Nitya Nand Gosvami, Sayan Ranu, Santiago Miret, N. M. Anoop Krishnan
2025	A*	`conf`	MatExpert: Decomposing Materials Discovery By Mimicking Human Experts. ICLR Qianggang Ding, Santiago Miret, Bang Liu
2025	J	`jnl`	OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction. CoRR Emily Jin, Andrei Cristian Nica, Mikhail Galkin, Jarrid Rector-Brooks, Kin Long Kelvin Lee, Santiago Miret, Frances H. Arnold, Michael M. Bronstein, Avishek Joey Bose, Alexander Tong, Cheng-Hao Liu
2025	J	`jnl`	Perspective on artificial intelligence for accelerated materials design (AI4Mat) workshops in 2024. Mach. Learn. Sci. Technol. Santiago Miret, Marta Skreta, Geemi P. Wellawatte, Stefano Martiniani, N. M. Anoop Krishnan, George Karypis, Kevin Maik Jablonka
2025	A*	`conf`	Stiefel Flow Matching for Moment-Constrained Structure Elucidation. ICLR Austin Henry Cheng, Alston Lo, Kin Long Kelvin Lee, Santiago Miret, Alán Aspuru-Guzik
2025	A*	`conf`	SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models. ICLR Daniel Levy, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Qiang Zhu, Kin Long Kelvin Lee, Mikhail Galkin, Santiago Miret, Siamak Ravanbakhsh
2025	J	`jnl`	SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models. CoRR Daniel Levy, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Qiang Zhu, Kin Long Kelvin Lee, Mikhail Galkin, Santiago Miret, Siamak Ravanbakhsh
2024	J	`jnl`	Are LLMs Ready for Real-World Materials Discovery? CoRR Santiago Miret, N. M. Anoop Krishnan
2024	J	`jnl`	Are large language models superhuman chemists? CoRR Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Benedict Emoekabu, Aswanth Krishnan, Mara Wilhelmi, Macjonathan Okereke, Juliane Eberhardt, Amir Mohammad Elahi, Maximilian Greiner, Caroline T. Holick, Tanya Gupta, Mehrdad Asgari, Christina Glaubitz, Lea C. Klepsch, Yannik Köster, Jakob Meyer, Santiago Miret, Tim Hoffmann, Fabian Alexander Kreth, Michael Ringleb, Nicole Roesner, Ulrich S. Schubert, Leanne M. Stafast, A. D. Dinga Wonanke, Michael Pieler, Philippe Schwaller, Kevin Maik Jablonka
2024	J	`jnl`	Deconstructing equivariant representations in molecular systems. CoRR Kin Long Kelvin Lee, Michael Galkin, Santiago Miret
2024	J	`jnl`	Foundational Large Language Models for Materials Research. CoRR Vaibhav Mishra, Somaditya Singh, Dhruv Ahlawat, Mohd Zaki, Vaibhav Bihani, Hargun Singh Grover, Biswajit Mishra, Santiago Miret, Mausam, N. M. Anoop Krishnan
2024	J	`jnl`	From Text to Insight: Large Language Models for Materials Science Data Extraction. CoRR Mara Schilling-Wilhelmi, Martiño Ríos-García, Sherjeel Shabih, María Victoria Gil, Santiago Miret, Christoph T. Koch, José A. Márquez, Kevin Maik Jablonka
2024	—	`conf`	HoneyComb: A Flexible LLM-Based Agent System for Materials Science. EMNLP (Findings) Huan Zhang, Yu Song, Ziyu Hou, Santiago Miret, Bang Liu
2024	J	`jnl`	HoneyComb: A Flexible LLM-Based Agent System for Materials Science. CoRR Huan Zhang, Yu Song, Ziyu Hou, Santiago Miret, Bang Liu
2024	J	`jnl`	MatExpert: Decomposing Materials Discovery by Mimicking Human Experts. CoRR Qianggang Ding, Santiago Miret, Bang Liu
2024	J	`jnl`	MatText: Do Language Models Need More than Text & Scale for Materials Modeling? CoRR Nawaf Alampara, Santiago Miret, Kevin Maik Jablonka
2024	J	`jnl`	PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design. J. Mach. Learn. Res. Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick
2024	A*	`conf`	Searching for High-Value Molecules Using Reinforcement Learning and Transformers. ICLR Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth
2024	J	`jnl`	Stiefel Flow Matching for Moment-Constrained Structure Elucidation. CoRR Austin H. Cheng, Alston Lo, Kin Long Kelvin Lee, Santiago Miret, Alán Aspuru-Guzik
2023	J	`jnl`	A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
2023	—	`conf`	Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model. EMNLP (Findings) Parishad BehnamGhader, Santiago Miret, Siva Reddy
2023	J	`jnl`	EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations. CoRR Vaibhav Bihani, Utkarsh Pratiush, Sajid Mannan, Tao Du, Zhimin Chen, Santiago Miret, Matthieu Micoulaut, Morten M. Smedskjaer, Sayan Ranu, N. M. Anoop Krishnan
2023	A*	`conf`	FAENet: Frame Averaging Equivariant GNN for Materials Modeling. ICML Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
2023	J	`jnl`	FAENet: Frame Averaging Equivariant GNN for Materials Modeling. CoRR Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
2023	—	`conf`	HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science. EMNLP (Findings) Yu Song, Santiago Miret, Huan Zhang, Bang Liu
2023	J	`jnl`	HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science. CoRR Yu Song, Santiago Miret, Huan Zhang, Bang Liu
2023	—	`conf`	MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling. ACL (1) Yu Song, Santiago Miret, Bang Liu
2023	J	`jnl`	MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling. CoRR Yu Song, Santiago Miret, Bang Liu
2023	J	`jnl`	MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling. CoRR Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings, Mikhail Galkin, Santiago Miret
2023	A*	`conf`	Multi-Objective GFlowNets. ICML Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
2023	J	`jnl`	On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions. CoRR Alvaro Carbonero, Alexandre Duval, Victor Schmidt, Santiago Miret, Alex Hernández-García, Yoshua Bengio, David Rolnick
2023	A*	`conf`	ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts. ICML Minghao Xu, Xinyu Yuan, Santiago Miret, Jian Tang
2023	J	`jnl`	ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts. CoRR Minghao Xu, Xinyu Yuan, Santiago Miret, Jian Tang
2023	J	`jnl`	Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance. CoRR Austin H. Cheng, Alston Lo, Santiago Miret, Brooks Pate, Alán Aspuru-Guzik
2023	J	`jnl`	Searching for High-Value Molecules Using Reinforcement Learning and Transformers. CoRR Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth
2023	J	`jnl`	The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science. Trans. Mach. Learn. Res. Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings
2023	—	`conf`	Towards Foundation Models for Materials Science: The Open MatSci ML Toolkit. SC Workshops Kin Long Kelvin Lee, Carmelo Gonzales, Matthew Spellings, Mikhail Galkin, Santiago Miret, Nalini Kumar
2023	J	`jnl`	Towards equilibrium molecular conformation generation with GFlowNets. CoRR Alexandra Volokhova, Michal Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca A. Thiede, Zichao Yan, Alán Aspuru-Guzik, Yoshua Bengio
2023	J	`jnl`	Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks. CoRR Daniel Levy, Sékou-Oumar Kaba, Carmelo Gonzales, Santiago Miret, Siamak Ravanbakhsh
2022	J	`jnl`	Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model. CoRR Parishad BehnamGhader, Santiago Miret, Siva Reddy
2022	J	`jnl`	Group SELFIES: A Robust Fragment-Based Molecular String Representation. CoRR Austin H. Cheng, Andy Cai, Santiago Miret, Gustavo Malkomes, Mariano Phielipp, Alán Aspuru-Guzik
2022	B	`conf`	Learning Intrinsic Symbolic Rewards in Reinforcement Learning. IJCNN Hassam Ullah Sheikh, Shauharda Khadka, Santiago Miret, Somdeb Majumdar, Mariano Phielipp
2022	J	`jnl`	Multi-Objective GFlowNets. CoRR Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
2022	A	`conf`	Neuroevolution-enhanced multi-objective optimization for mixed-precision quantization. GECCO Santiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phielipp, Nilesh Jain, Somdeb Majumdar
2022	J	`jnl`	PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design. CoRR Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick
2022	J	`jnl`	The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science. CoRR Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings
2021	J	`jnl`	Neuroevolution-Enhanced Multi-Objective Optimization for Mixed-Precision Quantization. CoRR Santiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phielipp, Nilesh Jain, Somdeb Majumdar
2021	A*	`conf`	Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning. ICLR Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang, Somdeb Majumdar
2020	A*	`conf`	Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination. ICML Somdeb Majumdar, Shauharda Khadka, Santiago Miret, Stephen McAleer, Kagan Tumer
2020	J	`jnl`	Learning Intrinsic Symbolic Rewards in Reinforcement Learning. CoRR Hassam Sheikh, Shauharda Khadka, Santiago Miret, Somdeb Majumdar
2020	J	`jnl`	Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning. CoRR Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Hanlin Tang, Shie Mannor, Tamir Hazan, Somdeb Majumdar
2020	J	`jnl`	Safety Aware Reinforcement Learning (SARL). CoRR Santiago Miret, Somdeb Majumdar, Carroll Wainwright
2019	A*	`conf`	Collaborative Evolutionary Reinforcement Learning. ICML Shauharda Khadka, Somdeb Majumdar, Tarek Nassar, Zach Dwiel, Evren Tumer, Santiago Miret, Yinyin Liu, Kagan Tumer
2019	J	`jnl`	Collaborative Evolutionary Reinforcement Learning. CoRR Shauharda Khadka, Somdeb Majumdar, Tarek Nassar, Zach Dwiel, Evren Tumer, Santiago Miret, Yinyin Liu, Kagan Tumer
2018	—	`—`	Computational Design of Ceramic Matrix Composites for Turbine Blade Applications Santiago Miret