ICML 2025 Past Other

Championing Open-source DEvelopment in ML Workshop @ ICML25

CODEML@ICML25

Submission deadline
May 27, 2025, 11:59 UTC
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Submission portal
OpenReview
Notes
Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).

Accepted papers (44)

Fetched from OpenReview (v2) on 2026-06-10.

  1. $\texttt{markovml}$: A Python Package for Verifying Markov Processes with Embedded Machine Learning Models

    Muhammad Maaz, Timothy Chan · PDF
  2. A2Perf: Benchmarking Autonomous Agents End-to-End in Realistic Domains

    Ikechukwu Uchendu, Jason Jabbour, Korneel Van den Berghe, Joel Runevic, Matthew Stewart, Jeffrey Jian Ma, Srivatsan Krishnan, Izzeddin Gur, Austin V Huang, Colton Bishop, Paige Bailey, Wenjie Jiang, Ebrahim Songhori, Sergio Guadarrama, Jie Tan, J K Terry, Aleksandra Faust, Vijay Janapa Reddi · PDF
  3. AIF-GEN: Open-Source Platform and Synthetic Dataset Suite for Reinforcement Learning on Large Language Models

    Jacob Chmura, Shahrad Mohammadzadeh, Ivan Anokhin, Jacob-Junqi Tian, Mandana Samiei, Taz Scott-Talib, Irina Rish, Doina Precup, Reihaneh Rabbany, Nishanth Anand · PDF
  4. An LLM-Powered Tool for Enhancing Scientific Open-Source Repositories

    Nikolay Nikitin, Andrey Getmanov, Zakhar Popov, Ulyanova Ekaterina Alekseevna, Yaroslav Aksenkin, Ilya Sokolov, Alexander Boukhanovsky · PDF
  5. An Open-Source Software Toolkit & Benchmark Suite for the Evaluation and Adaptation of Multimodal Action Models

    Pranav Guruprasad, Yangyue Wang, Jaewoo Song, Sudipta Chowdhury, Harsh Sikka · PDF
  6. Bencher: Simple and Reproducible Benchmarking for Black-Box Optimization

    Leonard Papenmeier, Luigi Nardi · PDF
  7. BoFire: Bayesian Optimization Framework Intended for Real Experiments

    Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte, Gabriel Mancino-Ball, Benjamin Schiller, Simon Sung, Julian Keupp, Aaron Paul Osburg, Toby Boyne, Ruth Misener, Rosona Eldred, Chrysoula Dimitra Kappatou, Robert Matthew Lee, Dominik Linzner, Wagner Steuer Costa, David Walz, Niklas Wulkow, Behrang Shafei · PDF
  8. Common Task Framework For a Critical Evaluation of Scientific Machine Learning Algorithms

    Philippe Martin Wyder, Judah Goldfeder, Alexey Yermakov, Yue Zhao, Stefano Riva, Jan P. Williams, David Zoro, Amy Sara Rude, Matteo Tomasetto, Joe Germany, Joseph Bakarji, Georg Maierhofer, Miles Cranmer, J. Nathan Kutz · PDF
  9. Control Flow Operators in PyTorch

    Yidi Wu, Thomas Ortner, Richard Zou, Edward Z. Yang, Adnan Akhundov, Horace He, Yanan Cao · PDF
  10. cp_measure: API-first feature extraction for image-based profiling workflows

    Alán F Muñoz, Tim Treis, Alexandr A. Kalinin, Shatavisha Dasgupta, Fabian J Theis, Anne E Carpenter, Shantanu Singh · PDF
  11. DeepChem-Variant: A Modular Open Source Framework for Genomic Variant Calling

    Ankita Vaishnobi Bisoi, Shreyas V, Jose Siguenza, Bharath Ramsundar · PDF
  12. Deploying User-Friendly Software: Six Recommendations to Make Single-Cell Foundation Models More Usable For Scientific Discovery

    Izumi Ando, Hassaan Maan, Kieran R. Campbell · PDF
  13. Developing and Maintaining an Open-Source Repository of AI Evaluations: Challenges and Insights

    Alexandra Abbas, Celia Waggoner, Justin Olive · PDF
  14. DINOHash: Learning Adversarially Robust Perceptual Hashes from Self-Supervised Features

    Shree Singhi, Aayush Gupta, Lukas Struppek · PDF
  15. DISCO: A Browser-Based Privacy-Preserving Framework for Distributed Collaborative Learning

    Julien Tuấn Tú Vignoud, Martin Jaggi, Mary-Anne Hartley, Tahseen Rabbani, Valérian Rousset · PDF
  16. EXO Gym: a simulation environment for low-bandwidth training

    Seth Howes, Matt Beton, Mohamed Baioumy, Alex Cheema, Matthew Reed · PDF
  17. FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems

    Val Andrei Fajardo, D. B. Emerson, Amandeep Singh, Marcelo Lotif, Veronica Chatrath, Izuki Matsuba, Chi Ho Cheung, Ravi Theja Desetty · PDF
  18. If open source is to win, it must go public

    Joshua Z Tan, Nicholas Vincent, Katherine Elkins, Magnus Sahlgren · PDF
  19. KernelBot: A Competition Platform for Writing Heterogeneous GPU Code

    Alex L Zhang, Matej Sirovatka, Erik Schultheis, Benjamin Horowitz, Mark Saroufim · PDF
  20. laplax - Laplace Approximations with JAX

    Tobias Weber, Bálint Mucsányi, Lenard Rommel, Thomas Christie, Lars Kasüschke, Marvin Pförtner, Philipp Hennig · PDF
  21. Liger-Kernel: Efficient Triton Kernels for LLM Training

    Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, Qingquan Song, Shao Tang, Siyu Zhu, Steven Shimizu, Shivam Sahni, Haowen Ning, Yanning Chen, Zhipeng Wang · PDF
  22. LUQ: Language Models Uncertainty Quantification Toolkit

    Alexander V Nikitin, Martin Trapp, Pekka Marttinen · PDF
  23. M(M)ORE : Massive Multimodal Open RAG & Extraction

    Alexandre Sallinen, Stefan Krsteski, Paul Teiletche, Allard Marc-Antoine, Baptiste Lecoeur, Michael Zhang, Fabrice Nemo, David Kalajdzic, Matthias Meyer, Mary-Anne Hartley · PDF
  24. Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks

    Isaac Chung, Imene Kerboua, Márton Kardos, Roman Solomatin, Kenneth Enevoldsen · PDF
  25. Meta-World+: An Improved, Standardized, RL Benchmark

    Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon, Frank Röder, Tianhe Yu, Zhanpeng He, K.R. Zentner, Ryan Julian, J K Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro · PDF
  26. N$^2$: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion

    Caleb Chin, Aashish Khubchandani, Harshvardhan Maskara, Kyuseong Choi, Jacob Feitelberg, Albert Gong, Manit Paul, Tathagata Sadhukhan, Anish Agarwal, Raaz Dwivedi · PDF
  27. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models

    Jake Poznanski, Aman Rangapur, Jon Borchardt, Jason Dunkelberger, Christopher Wilhelm, Kyle Lo, Luca Soldaini · PDF
  28. Open-Source Foosball Benchmark for Deep Reinforcement Learning

    Matthew So, Kwansoo Lee, Judah Goldfeder, Hod Lipson · PDF
  29. Orthogonium: A Unified, Efficient Library of Orthogonal and 1‑Lipschitz Building Blocks

    Thibaut Boissin, Franck Mamalet, Valentin Lafargue, Mathieu Serrurier · PDF
  30. Provenance Design and Evolution in a Production ML Library

    Adam Craig Pocock, Joseph Wonsil, Romina Mahinpei, Jack Sullivan, Margo Seltzer · PDF
  31. PyLO: Towards Accessible Learned Optimizers in Pytorch

    Paul Janson, Benjamin Thérien, Quentin Gregory Anthony, Xiaolong Huang, Abhinav Moudgil, Eugene Belilovsky · PDF
  32. RepoST: Scalable Repository-Level Coding Environment Construction with Sandbox Testing

    Yiqing Xie, Alex Xie, Divyanshu Sheth, Pengfei Liu, Daniel Fried, Carolyn Rose · PDF
  33. Reproducible sampling from intractable distributions with Pigeons.jl

    Miguel Biron-Lattes, Nikola Surjanovic, Paul Tiede, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Côté · PDF
  34. SAGDA: Open-Source Synthetic Agriculture Data for Africa

    Abdelghani Belgaid, Oumnia Ennaji · PDF
  35. Scaling Private Deep Learning with Opacus: Advances for Large Language Models

    Sai Aparna Aketi, Will Bullock, Iden Kalemaj, Enayat Ullah, Huanyu Zhang · PDF
  36. skglm: Improving scikit-learn for Regularized Generalized Linear Models

    Mathurin Massias, Badr MOUFAD, Quentin Bertrand · PDF
  37. Spatial Reasoners for Continuous Variables in Any Domain

    Bart Pogodzinski, Christopher Wewer, Bernt Schiele, Jan Eric Lenssen · PDF
  38. Swizz: One-Liner Figures, LaTeX Tables, and Flexible Layouts for Scientific Papers

    Lars C.P.M. Quaedvlieg, Andrea Miele, Caglar Gulcehre · PDF
  39. TGM: A Modular Framework for Machine Learning on Temporal Graphs

    Jacob Chmura, Shenyang Huang, Ali Parviz, Farimah Poursafaei, Michael M. Bronstein, Guillaume Rabusseau, Matthias Fey, Reihaneh Rabbany · PDF
  40. TorchAO: PyTorch-Native Training-to-Serving Model Optimization

    Andrew Or, Apurva Jain, Daniel Vega-Myhre, Jesse Cai, Charles David Hernandez, Zhenrui Zhang, Driss Guessous, Vasiliy Kuznetsov, Christian Puhrsch, Mark Saroufim, Supriya Rao · PDF
  41. TorchTitan: A PyTorch Native Platform for Training Generative AI Models

    Tianyu Liu, Wanchao Liang · PDF
  42. Vulnerability of Text-Matching in ML/AI Conference Reviewer Assignments to Collusions

    Jhih-Yi Hsieh, Aditi Raghunathan, Nihar B Shah · PDF
  43. Write Code that People Want to Use

    Stella Biderman, Jennifer Mickel, Baber Abbasi · PDF
  44. ZKLoRA: Efficient Zero-Knowledge Proofs for LoRA Verification

    Bidhan Roy, Peter Potash, Marcos Villagra · PDF