Announcing the NeurIPS 2026 Journal Track
Announcing the NeurIPS 2026 Journal Track
The NeurIPS Journal Track aims to strengthen the bridge between machine learning and statistics communities and enable the dissemination of scientific knowledge. Journals such as Journal of Machine Learning Research (JMLR), Transactions on Machine Learning Research (TMLR), and Annals of Statistics (AoS) accept rigorously reviewed papers on a rolling schedule outside of the conference cycle. This track allows the accepted papers of these journals to also be presented at NeurIPS to get increased visibility and spark discussion.
This year, we are thrilled to feature 88 accepted papers: 64 from the Transactions on Machine Learning Research (TMLR), 16 from the Journal of Machine Learning Research (JMLR), and 8 from the Annals of Statistics (AoS), all of which will be presented across our conference locations in Sydney, Atlanta, and Paris this December at the main conference event, alongside the Main Track, and Evaluations & Datasets Track. These papers represent high standards across theory, methodology, and applications, and they exemplify how journal-based research continues to enrich the broader NeurIPS community.
We invite all attendees to visit the Journal Track poster presentations, meet the authors, and engage in discussions that highlight the evolving connections between machine learning and statistics.
Accepted Papers from the Transactions on Machine Learning Research (TMLR)
1) A Multi-Fidelity Control Variate Approach for Policy Gradient Estimation
Xinjie Liu, Cyrus Neary, Kushagra Gupta, Wesley A. Suttle, Christian Ellis, Ufuk Topcu, David Fridovich-Keil
https://openreview.net/forum?id=zAo0L7Dcqt
2) Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding
Jiaru Zhang, Juanwu Lu, Xiaoyu Wu, Ziran Wang, Ruqi Zhang
https://openreview.net/forum?id=xYATz9HpE7
3) Achieving adaptivity and optimality for multi-armed bandits using Exponential-Kullback Leibler Maillard Sampling
Hao Qin, Kwang-Sung Jun, Chicheng Zhang
https://arxiv.org/abs/2502.14379
4) Align and Distill: Unifying and Improving Domain Adaptive Object Detection
Justin Kay, Timm Haucke, Suzanne Stathatos, Siqi Deng, Erik Young, Pietro Perona, Sara Beery, Grant Van Horn
https://openreview.net/forum?id=ssXSrZ94sR
5) Continual Robot Learning via Language-Guided Skill Acquisition
Shuo Cheng, Zhaoyi Li, Kelin Yu, Danfei Xu
https://openreview.net/pdf?id=oYRNxxGN9u
6) Discovering Symbolic Differential Equations with Symmetry Invariants
Jianke Yang, Manu Bhat, Bryan Hu, Yadi Cao, Nima Dehmamy, Robin Walters, Rose Yu
https://openreview.net/forum?id=9t1dEyYfPc
7) FedIndex: Federated Domain Adaptation with Continuous Domain Indices
Qingyang Yu, Hao Wang, Qizhen Zhang, Hao Wang
https://openreview.net/forum?id=fnbGFH0330
8) Generalized Smooth Stochastic Variational Inequalities: Almost Sure Convergence and Convergence Rates
Daniil Vankov, Angelia Nedich, Lalitha Sankar
https://openreview.net/forum?id=EjqSpbUBWU
9) HDCS: Hierarchy Discovery and Critic Shaping for Reinforcement Learning with Automaton Specification
Duo Xu, Farmarz Fekri
https://openreview.net/forum?id=BGoRme2MfG
10) On the Convergence Analysis of Muon
Wei Shen, Ruichuan Huang, Minhui Huang, Cong Shen, Jiawei Zhang
https://openreview.net/forum?id=4nH4CulGaP
11) OpInf-LLM: Parametric PDE Solving with LLMs via Operator Inference
Zhuoyuan Wang, Hanjiang Hu, Xiyu Deng, Saviz Mowlavi, Yorie Nakahira
https://openreview.net/forum?id=rCTRgstMr1
12) Paradoxical noise preference in RNNs
Noah Izaac Eckstein, Manoj Srinivasan
https://openreview.net/pdf?id=gqxTZRzI35
13) Rational Tuning of LLM Cascades via Probabilistic Modeling
Michael J. Zellinger, Matt Thomson
https://openreview.net/forum?id=YCBVcGSZeR
14) RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance
Miao Lin, Feng Yu, Rui Ning, Lusi Li, Jiawei Chen, Qian Lou, Mengxin Zheng, Chunsheng Xin, Hongyi Wu
https://openreview.net/forum?id=WyPkotlgqQ
15) TextRegion: Text-Aligned Region Tokens from Frozen Image-Text Models
Yao Xiao, Qiqian Fu, Heyi Tao, Yuqun Wu, Zhen Zhu, Derek Hoiem
https://openreview.net/pdf?id=KZLmkL62M4
16) Understanding the Effects of Neuron Dominance in Deep Reinforcement Learning
Zifan Wu, Qian Lin, Blake Lawlor, Haijun Zhao, Daniel S. Brown
https://openreview.net/forum?id=VNV1h77UnH
17) What Should Embeddings Embed? Autoregressive Models Represent Latent Generating Distributions
Liyi Zhang, Michael Y. Li, R. Thomas McCoy, Theodore R. Sumers, Jian-Qiao Zhu, Thomas L. Griffiths
https://openreview.net/pdf?id=YyMACp98Kz
18) AdaCubic: An Adaptive Cubic Regularization Optimizer for Deep Learning
Ioannis Tsingalis, Constantine Kotropoulos, Corentin Briat
https://openreview.net/forum?id=pZBQ7J37lk
19) ARC-Encoder: learning compressed text representations for large language models
Hippolyte Pilchen, Edouard Grave, Patrick Perez
https://openreview.net/forum?id=lU1P9dsqfn
20) Attention Trajectories as a Diagnostic Axis for Deep Reinforcement Learning
Charlotte Beylier, Hannah Selder, Arthur Fleig, Simon M. Hofmann, Nico Scherf
https://openreview.net/forum?id=0aa9zthk7k
21) Autofocus Retrieval: An Effective Pipeline for Multi-Hop Question Answering With Semi-Structured Knowledge
Derian Boer, Stephen Linus Roth, Stefan Kramer
https://openreview.net/forum?id=U2vqruHfQY
22) Beyond the Linear Separability Ceiling: Aligning Representations in VLMs
Enrico Vompa, Tanel Tammet, Mohit Vaishnav
https://openreview.net/pdf?id=3uX4p80bN0
23) Differentiable Cluster Discovery in Temporal Graphs
Md Hafizur Rahman, Chi-Guhn Lee
https://openreview.net/forum?id=1caZVb6zL7
24) Exploring the Limitations of Layer Synchronization in Spiking Neural Networks
Roel Koopman, Amirreza Yousefzadeh, Mahyar Shahsavari, Guangzhi Tang, Manolis Sifalakis
https://openreview.net/pdf?id=mfmAVwtMIk
25) FusionProt: Fusing Sequence and Structural Information for Unified Protein Representation Learning
Dan Kalifa, Uriel Singer, Kira Radinsky
https://openreview.net/pdf?id=imcinaOHod
26) Many Circuits, One Mechanism: Input Variation and Evaluation Granularity in Circuit Discovery
Alireza Bayat Makou, Jingcheng Niu, Subhabrata Dutta, Iryna Gurevych
https://openreview.net/forum?id=Ur42Xx1QPv
27) MatchEx: Model-Level GNN Explanations with Multi-Granular Insights
Sayan Saha, Sanghamitra Bandyopadhyay
https://openreview.net/pdf?id=YMETLG2WvM
28) Neural Fourier Transform for Multiple Time Series Prediction
Noam Koren, Daniel Freedman, Kira Radinsky
https://openreview.net/forum?id=0GBjIwRuVp
29) On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
Balázs Csanád Csáji, László Györfi, Ambrus Tamás, Harro Walk
https://openreview.net/pdf?id=KYYvIrtgK0
30) On the Expressive Power and Limitations of Multi-Layer SSMs
Nikola Zubić, Qian Li, Yuyi Wang, Davide Scaramuzza
https://openreview.net/forum?id=NQ8IcsIti8
31) Regret minimization in Linear Bandits with offline data via extended D-optimal exploration.
Sushant Vijayan, Arun Suggala, Karthikeyan Shanmugam, Soumyabrata Pal
https://openreview.net/forum?id=4WcK8gKgCi
32) Think2SQL: Blueprinting Reward Density and Advantage Scaling for Effective Text-to-SQL Reasoning
Simone Papicchio, Simone Rossi, Luca Cagliero, Paolo Papotti
https://openreview.net/forum?id=NxU1KWnpOG
33) TropNNC: Structured Neural Network Compression Using Tropical Geometry
Konstantinos Fotopoulos, Petros Maragos, Panagiotis Misiakos
https://openreview.net/forum?id=u7DRq1icmY
34) Active Learning via Classifier Impact and Greedy Selection for Interactive Image Retrieval
Leah Bar, Boaz Lerner, Nir Darshan, Rami Ben-Ari
https://arxiv.org/abs/2412.02310
35) ARROW: Augmented Replay for RObust World models
Abdulaziz Alyahya, Abdallah Al Siyabi, Markus R. Ernst, Luke Yang, Levin Kuhlmann, Gideon Kowadlo
https://openreview.net/pdf?id=3FK2tFwNwK
36) ASAT: Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection
Daisuke Yamada, Harit Vishwakarma, Ramya Korlakai Vinayak
https://openreview.net/forum?id=4Kd0VMsL76
37) Below the Reliability Floor: Recovering True Success from Judge-Gated Loops
Tautik Agrahari, Jeff Joji
https://openreview.net/forum?id=J2Yg9vJcYb
38) Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens
Karthik Valmeekam, Vardhan Palod, Kaya Stechly, Atharva Gundawar, Subbarao Kambhampati
https://openreview.net/forum?id=gDE7YcRC3F
39) Bigger Isn’t Always Memorizing: Early Stopping Overparameterized Diffusion Models
Alessandro Favero, Antonio Sclocchi, Matthieu Wyart
https://openreview.net/pdf?id=P6r9OxZ1vm
40) Classification of high-dimensional data with spiked covariance matrix structure
Yin-Jen Chen, Minh Tang
https://openreview.net/forum?id=6bQDtTbaQs
41) DecompDreamer: A Composition-Aware Curriculum for Structured 3D Asset Generation
Utkarsh Nath, Rajeev Goel, Rahul Khurana, Kyle Min, Mark Ollila, Pavan Turaga, Varun Jampani, Tejaswi Gowda
https://openreview.net/pdf?id=3qy4J6QFbn
42) Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
Raghav Singhal, Kaustubh Ponkshe, Rohit Vartak, Lav R. Varshney, Praneeth Vepakomma
https://openreview.net/forum?id=87UyFEhzyP
43) Few Contrastive Attention Heads Enable Visual Grounding in Large Vision-Language Models
Neha Sengar, Andres Saurez, Dongsoo Har, Sangkeum Lee
https://openreview.net/forum?id=CnrAiXbw8a
44) In-context Learning in Presence of Spurious Correlations
Hrayr Harutyunyan, Rafayel Darbinyan, Samvel Karapetyan, Hrant Khachatrian
https://openreview.net/forum?id=C9CSaTR1iA
45) Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization
Minttu Alakuijala, Ya Gao, Georgy Ananov, Samuel Kaski, Pekka Marttinen, Alexander Ilin, Harri Valpola
https://openreview.net/forum?id=AtCURrC3XA
46) Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning
Vinayak Vinayak, Ananyae Kumar bhartari, Vivek Shenoy
https://openreview.net/forum?id=6mFVZSzyev
47) No Detail Left Behind: Revisiting Self-Retrieval for Fine-Grained Image Captioning
Manu Gaur, Darshan Singh S, Makarand Tapaswi
https://openreview.net/forum?id=gqh0yzPYdo
48) On Fitting Flow Models with Large Sinkhorn Couplings
Stephen Zhang, Alireza Mousavi-Hosseini, Michal Klein, Marco Cuturi
https://openreview.net/forum?id=3MLKJZgY62
49) OTIS: Learning High-Quality Time Series Features With Tiny Encoders
Özgün Turgut, Philip Müller, Martin J. Menten, Daniel Rueckert
https://openreview.net/pdf?id=WW206A1Tru
50) Random features for Grassmannian kernel approximation with bounded rank-one projections
Remi Delogne, Laurent Jacques
https://openreview.net/forum?id=wq18dZJ2pA
51) Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models
Hung Le, Van Dai Do, Dung Nguyen, Svetha Venkatesh
https://openreview.net/forum?id=tmdwuU2uKs
52) Replicability is Asymptotically Free in Multi-armed Bandits
Junpei Komiyama, Shinji Ito, Yuichi Yoshida, Souta Koshino
https://openreview.net/forum?id=E8rmbq8BYP
53) RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent
Cheng Fang, Rishabh Dixit, Waheed U. Bajwa, Mert Gürbüzbalaban
https://openreview.net/forum?id=aNu8S9O6Ug
54) Rethinking Reward Models for Multi-Domain Test-Time Scaling
Dong Bok Lee, Seanie Lee, Sangwoo Park, Minki Kang, Jinheon Baek, Dongki Kim, Dominik Wagner, Jiongdao Jin, Heejun Lee, Tobias Bocklet, Jinyu Wang, Jingjing Fu, Sung Ju Hwang, Jiang Bian, Lei Song
https://openreview.net/forum?id=PgouBhL7IR
55) Rethinking the Mixture of Vision Encoders Paradigm for Enhanced Visual Understanding in Multimodal LLMs
Mozhgan Nasr Azadani, James Riddell, Sean Sedwards, Krzysztof Czarnecki
https://openreview.net/forum?id=tgnTVmRybs
56) RSQ: Learning from Important Tokens Leads to Better Quantized LLMs
Yi-Lin Sung, Prateek Yadav, Jialu Li, Jaehong Yoon, Mohit Bansal
https://openreview.net/forum?id=kBezrKXHVS
57) SAMAT: A Stereotype-Aware Multimodal Transformer for Interpretable Misogynistic Meme Detection
Gopendra Vikram Singh, Arpan Phukan, Kushal Kanwar, Asif Ekbal
https://openreview.net/forum?id=1DJBFS7rLW
58) T3-S2S: Training-free Triplet Tuning for Sketch to Scene Generation
Zhenhong Sun, Yifu Wang, Yonhon Ng, Yongzhi Xu, Daoyi Dong, Hongdong Li, Pan Ji
https://openreview.net/forum?id=lyn2BgKQ8F
59) The Confusion is Real: GRAPHIC – A Network Science Approach to Confusion Matrices in Deep Learning
Johanna S. Fröhlich, Bastian Heinlein, Jan U. Claar, Hans Rosenberger, Vasileios Belagiannis, Ralf R. Müller
https://openreview.net/forum?id=UP9bx1WJwR
60) The Foundation Model Transparency Index
Rishi Bommasani, Kevin Klyman, Shayne Longpre, Sayash Kapoor, Nestor Maslej, Betty Xiong, Daniel Zhang, Percy Liang
https://arxiv.org/abs/2310.12941
61) The Internal Growth Function: A More General PAC Framework for Scenario Decision Making
Guillaume O. Berger, Raphaël M. Jungers
https://openreview.net/forum?id=HqPKJSAkrp
62) Towards Principled Task Grouping for Multi-Task Learning
Chenguang Wang, Xuanhao Pan, Tianshu Yu
https://openreview.net/pdf?id=3DeSIpzuro
63) Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback
Jungtaek Kim, Thomas Zeng, Ziqian Lin, Minjae Lee, Chungpa Lee, Jy-yong Sohn, Hyung Il Koo, Kangwook Lee
https://openreview.net/forum?id=Jij7zCjVfc
64) VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild
Junlin Fang, Wenyu Chen, Reshmi Ghosh, Robert Sim, Ahmed Salem, Vitor R. Carvalho, Emily Lawton, Sharon Li, Jack W. Stokes, Sean Du
https://openreview.net/forum?id=z7gczmhmmo
Accepted Papers from the Journal of Machine Learning Research (JMLR)
1) Almost Sure Convergence of Linear Temporal Difference Learning with Arbitrary Features
Jiuqi Wang, Shangtong Zhang
https://www.jmlr.org/papers/v27/24-1538.html
2) The Z-Gromov-Wasserstein Distance
Martin Bauer, Facundo Mémoli, Tom Needham, Mao Nishino
https://jmlr.org/papers/v26/24-2189.html
3) Corruptions of Supervised Learning Problems: Typology and Mitigations
Laura Iacovissi, Nan Lu, Robert C. Williamson
https://jmlr.org/papers/v27/24-0808.html
4) Demographic parity in regression and classification within the unawareness framework
Vincent Divol, Solenne Gaucher
https://www.jmlr.org/papers/volume27/24-1338/24-1338.pdf
5) DINOv3
Oriane Siméoni, Huy V Vo, Maximilian Seitzer, Federico Baldassarre, Maxime Oquab, Cijo Jose, Vasil Khalidov, Marc Szafraniec, Seungeun Yi, Michaël Ramamonjisoa, Francisco Massa, Daniel Haziza, Luca Wehrstedt, Jianyuan Wang, Timothée Darcet, Théo Moutakanni, Leonel Sentana, Claire Roberts, Andrea Vedaldi, Jamie Tolan, John Brandt, Camille Couprie, Julien Mairal, Hervé Jégou, Patrick Labatut, Piotr Bojanowski
https://openreview.net/pdf?id=2NlGyqNjns
6) Gradient Span Algorithms Make Predictable Progress in High Dimension
Felix Benning, Leif Döring
https://www.jmlr.org/papers/v27/25-1651.html
7) An Anytime Algorithm for Good Arm Identification
Marc Jourdan, Andrée Delahaye-Duriez, Clémence Réda
https://jmlr.org/papers/v27/24-0680.html
8) Online Bernstein-von Mises theorem
Jeyong Lee, Junhyeok Choi, Minwoo Chae
https://jmlr.org/papers/volume27/25-0989/25-0989.pdf
9) Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters
Sebastian Salwig, Till Kahlke, Florian Hirschberger, Dennis Forster, Jörg Lücke
https://jmlr.org/papers/v27/25-0639.html
10) “What is Different Between These Datasets?” A Framework for Explaining Data Distribution Shifts
Varun Babbar, Zhicheng Guo, Cynthia Rudin
https://jmlr.org/papers/v26/24-0352.html
11) Global convergence of adjoint-optimized neural PDEs
Konstantin Riedl, Justin Sirignano, Konstantinos Spiliopoulos
https://www.jmlr.org/papers/v26/25-1383.html
12) Guaranteed Nonconvex Low-Rank Tensor Estimation via Scaled Gradient Descent
Tong Wu
https://www.jmlr.org/papers/v27/25-0012.html
13) Minimax Optimal Two-Sample Testing under Local Differential Privacy
Jongmin Mun, Seungwoo Kwak, Ilmun Kim
https://jmlr.org/papers/v26/24-2016.html
14) Multiple Instance Verification
Xin Xu, Eibe Frank, Geoffrey Holmes
https://www.jmlr.org/papers/v26/23-1590.html
15) Nonparametric Estimation of a Factorizable Density using Diffusion Models
Hyeok Kyu Kwon, Dongha Kim, Ilsang Ohn, Minwoo Chae
https://www.jmlr.org/papers/v27/25-0121.html
16) Statistical field theory for Markov decision processes under uncertainty
George Stamatescu
https://www.jmlr.org/papers/v26/23-0905.html
Accepted Papers from the Annals of Statistics (AoS)
1) DiPMInd: Distance profile based mutual independence testing for random objects
Yaqing Chen, Paromita Dubey
2) Generalized Robust Adaptive-Bandwidth Multi-View Manifold Learning in High Dimensions with Noise
Xiucai Ding, Chao Shen, Hau-Tieng Wu
https://arxiv.org/pdf/2602.10530
3) Gradient descent inference in empirical risk minimization
Qiyang Han, Xiaocong Xu
4) Smooth Flow Matching for Synthesizing Functional Data
Jianbin Tan, Anru Zhang
https://www.e-publications.org/ims/submission/AOS/user/submissionFile/74045?confirm=cf07e923
5) Fast Wasserstein rates for estimating probability distributions of probabilistic graphical models
Daniel Bartl, Stephan Eckstein
6) Privacy Guarantees in Posterior Sampling under Contamination
Shenggang Hu, Hongsheng Dai, Louis Aslett, Murray Pollock, Gareth O. Roberts
7) Consistent Bayesian Spatial Domain Partitioning Using Predictive Spanning Tree Methods
Kun Huang, Huiyan Sang
8) Spectral Asymptotics of Neural Network Jacobians: Convergency, Universality, and Phase Transition
Huiqin Li, Guangming Pan, Yanqing Yin
https://www.e-publications.org/ims/submission/AOS/user/submissionFile/71281?confirm=ca86d376
These presentations highlight the growing collaboration between NeurIPS and the leading journals that define our field. We look forward to welcoming all authors and attendees this December for an inspiring exchange of ideas that bridges deep theory, rigorous methods, and transformative applications.
NeurIPS 2026 Journal Track Chairs
Lam Nguyen, Masahiro Ikeda