Workshop on Neural Network Weights as a New Data Modality

Accepted papers (45)

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

1. A Model Zoo of Vision Transformers

   Damian Falk, Léo Meynent, Florence Pfammatter, Konstantin Schürholt, Damian Borth

2. A Model Zoo on Phase Transitions in Neural Networks

   Konstantin Schürholt, Léo Meynent, Yefan Zhou, Yaoqing Yang, Damian Borth

3. A Single Global Merging Suffices: Recovering Centralized Learning Performance in Decentralized Learning

   Tongtian Zhu, Tianyu Zhang, Mingze Wang, Zhanpeng Zhou, Can Wang

4. Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space

   Vinicius Hernandes, Thomas Spriggs, Saqar Khaleefah, Eliska Greplova

5. Adversarial Robustness in Parameter-Space Classifiers

   Tamir Shor, Ethan Fetaya, Chaim Baskin, Alex M. Bronstein

6. ARC: Anchored Representation Clouds for High-Resolution INR Classification

   Joost Luijmes, Alexander Gielisse, Roman Knyazhitskiy, Jan van Gemert

7. Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights

   Jonathan Kahana, Or Nathan, Eliahu Horwitz, Yedid Hoshen

8. Can We Optimize Deep RL Policy Weights as Trajectory Modeling?

   Hongyao Tang

9. Collaborative Time Series Imputation through Meta-learned Implicit Neural Representations

   Tong Nie, Wei Ma

10. Compressive Meta-Learning

    Daniel Mas Montserrat, David Bonet, Maria Perera, Xavier Giró-i-Nieto, Alexander G. Ioannidis

11. Cost-Efficient Continual Learning with Sufficient Exemplar Memory

    Dong Kyu Cho, Taesup Moon, Rumi Chunara, Kyunghyun Cho, Sungmin Cha

12. Dataset Size Recovery from Fine-Tuned Model Weights

    Mohammad Salama, Jonathan Kahana, Eliahu Horwitz, Yedid Hoshen

13. End-to-End Synthesis of Neural Programs in Weight Space

    Wenhao Li, Yudong Xu, Elias Boutros Khalil, Scott Sanner

14. Equivariant Neural Functional Networks for Transformers

    Hoang V. Tran, Thieu Vo, An Nguyen The, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen

15. Finding Stable Subnetworks at Initialization with Dataset Distillation

    Luke McDermott, Rahul Parhi

16. Flow to Learn: Flow Matching on Neural Network Parameters

    Daniel Saragih, Deyu Cao, Tejas Balaji, Ashwin Santhosh

17. Fusion of Graph Neural Networks via Optimal Transport

    Weronika Ormaniec, Michael Vollenweider, Elisa Hoskovec

18. GNNMERGE: MERGING OF GNN MODELS WITHOUT ACCESSING TRAINING DATA

    Vipul Garg, Ishita Thakre, Sayan Ranu

19. GradMetaNet: An Equivariant Architecture for Learning on Gradients

    Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Haggai Maron

20. Hyper-Align: Efficient Modality Alignment via Hypernetworks

    Jaisidh Singh, Diganta Misra, Boris Knyazev, Antonio Orvieto

21. Improving Learning to Optimize Using Parameter Symmetries

    Guy Zamir, Aryan Dokania, Bo Zhao, Rose Yu

22. Instruction-Guided Autoregressive Neural Network Parameter Generation

    Bedionita Soro, Bruno Andreis, Song Chong, Sung Ju Hwang

23. Integrating Meta-Trained Hypernetworks with GBDTs and Retrieval for Tabular Data

    David Bonet, Marçal Comajoan Cara, Alvaro Calafell, Daniel Mas Montserrat, Alexander G. Ioannidis

24. Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces

    Yihuai Hong, Lei Yu, Haiqin Yang, Shauli Ravfogel, Mor Geva

25. Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models

    Theo Putterman, Derek Lim, Yoav Gelberg, Stefanie Jegelka, Haggai Maron

26. Learning on Model Weights using Tree Experts

    Eliahu Horwitz, Bar Cavia, Jonathan Kahana, Yedid Hoshen

27. Mimetic Initialization Helps State Space Models Learn to Recall

    Asher Trockman, Hrayr Harutyunyan, J Zico Kolter, Sanjiv Kumar, Srinadh Bhojanapalli

28. Mimetic Initialization of MLPs

    Asher Trockman, J Zico Kolter

29. Model Assembly Learning with Heterogeneous Layer Weight Merging

    Yi-Kai Zhang, Jin Wang, Xu-Xiang Zhong, De-Chuan Zhan, Han-Jia Ye

30. Model Diffusion for Certifiable Few-shot Transfer Learning

    Fady Rezk, Royson Lee, Henry Gouk, Timothy Hospedales, Minyoung Kim

31. On Symmetries in Convolutional Weights

    Bilal Alsallakh, Timothy J Wroge, Vivek Miglani, Narine Kokhlikyan

32. On the internal representations of graph metanetworks

    Taesun Yeom, Jaeho Lee

33. ProDiF: Protecting Domain-Invariant Features to Secure Pre-Trained Models Against Extraction

    Tong Zhou, Shijin Duan, Gaowen Liu, Charles Fleming, Ramana Rao Kompella, Shaolei Ren, Xiaolin Xu

34. Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective

    Ambarish Moharil, Indika Kumara, Majid Mohammadi, Damian Andrew Tamburri, Willem-Jan van den Heuvel

35. Scaling Up Parameter Generation: A Recurrent Diffusion Approach

    Kai Wang, Dongwen Tang, Wangbo Zhao, Konstantin Schürholt, Zhangyang Wang, Yang You

36. Shape Generation via Weight Space Learning

    Maximilian Plattner, Arturs Berzins, Johannes Brandstetter

37. Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction

    Léo Meynent, Ivan Melev, Konstantin Schürholt, Goeran Kauermann, Damian Borth

38. TeleLoRA: Teleporting Alignment across Large Language Models for Trojan Mitigation

    Xiao Lin, Manoj Acharya, Anirban Roy, Susmit Jha

39. Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization

    Zexi Li, Lingzhi Gao, Chao Wu

40. The Empirical Impact of Reducing Symmetries on the Performance of Deep Ensembles and MoE

    Andrei Chernov, Oleg Novitskij

41. The Impact of Model Zoo Size and Composition on Weight Space Learning

    Damian Falk, Konstantin Schürholt, Damian Borth

42. The Space Between: On Folding, Symmetries and Sampling

    Michal Lewandowski, Bernhard Heinzl, Raphael Pisoni, Bernhard A. Moser

43. Uncovering Latent Chain of Thought Vectors in Large Language Models

    Jason Zhang, Scott W Viteri

44. Unveiling the Potential of Superexpressive Networks in Implicit Neural Representations

    Uvini Balasuriya Mudiyanselage, Woojin Cho, Minju Jo, Noseong Park, Kookjin Lee

45. Vanishing Feature: Diagnosing Model Merging and Beyond

    Xingyu Qu, Samuel Horváth