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NeurIPS 2025: all accepted papers

5,819 papers · page 30 of 59 · the most cited first · ← NeurIPS 2025

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  1. DeltaProduct: Improving State-Tracking in Linear RNNs via Householder Products ↗Julien Siems, Timur Carstensen, Arber Zela et al.
  2. Delving into Large Language Models for Effective Time-Series Anomaly Detection ↗JUN WOO PARK, Kyudan Jung, Dohyun Lee et al.
  3. Democratizing Clinical Risk Prediction with Cross-Cohort Cross-Modal Knowledge Transfer ↗Qiannan Zhang, Manqi Zhou, Zilong Bai et al.
  4. Demystifying Language Model Forgetting with Low-rank Example Associations ↗Xisen Jin, Xiang Ren
  5. Demystifying Network Foundation Models ↗Roman Beltiukov, Satyandra Guthula, Wenbo Guo et al.
  6. Demystifying Reasoning Dynamics with Mutual Information: Thinking Tokens are Information Peaks in LLM Reasoning ↗Chen Qian, Dongrui Liu, Haochen Wen et al.
  7. Demystifying Spectral Feature Learning for Instrumental Variable Regression ↗Dimitri Meunier, Antoine Moulin, Jakub Wornbard et al.
  8. Dendritic Resonate-and-Fire Neuron for Effective and Efficient Long Sequence Modeling ↗Dehao Zhang, Malu Zhang, Shuai Wang et al.
  9. DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentration ↗Tianteng Gu, Bei Liu, Bo Xiao et al.
  10. Denoising Trajectory Biases for Zero-Shot AI-Generated Image Detection ↗Yachao Liang, Min Yu, Gang Li et al.
  11. Dense Associative Memory with Epanechnikov Energy ↗Benjamin Hoover, Zhaoyang Shi, Krishnakumar Balasubramanian et al.
  12. Dense Backpropagation Improves Training for Sparse Mixture-of-Experts ↗Ashwinee Panda, Vatsal Baherwani, Zain Sarwar et al.
  13. Dense Metric Depth Estimation via Event-based Differential Focus Volume Prompting ↗Boyu Li, Peiqi Duan, Zhaojun Huang et al.
  14. Dense SAE Latents Are Features, Not Bugs ↗Xiaoqing Sun, Alessandro Stolfo, Joshua Engels et al.
  15. Density Ratio-Free Doubly Robust Proxy Causal Learning ↗Bariscan Bozkurt, Houssam Zenati, Dimitri Meunier et al.
  16. Dependency Matters: Enhancing LLM Reasoning with Explicit Knowledge Grounding ↗Xiangyu Wen, Min Li, Junhua Huang et al.
  17. Dependency Parsing is More Parameter-Efficient with Normalization ↗Paolo Gajo, Domenic Rosati, Hassan Sajjad et al.
  18. Deployment Efficient Reward-Free Exploration with Linear Function Approximation ↗Zihan Zhang, Yuxin Chen, Jason D. Lee et al.
  19. Depth-Supervised Fusion Network for Seamless-Free Image Stitching ↗Zhiying Jiang, Ruhao Yan, Zengxi Zhang et al.
  20. Depth-Width Tradeoffs for Transformers on Graph Tasks ↗Gilad Yehudai, Clayton Sanford, Maya Bechler-Speicher et al.
  21. DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches ↗Yun Xing, Yue Cao, Nhat Chung et al.
  22. Design-Based Bandits Under Network Interference: Trade-Off Between Regret and Statistical Inference ↗Zichen Wang, Haoyang Hong, Chuanhao Li et al.
  23. Detecting Data Deviations in Electronic Health Records ↗Kaiping Zheng, Horng‐Ruey Chua, Beng Chin Ooi
  24. Detecting High-Stakes Interactions with Activation Probes ↗Alex McKenzie, Urja Pawar, Philipp Blandfort et al.
  25. DetectiumFire: A Comprehensive Multi-modal Dataset Bridging Vision and Language for Fire Understanding ↗Zixuan Liu, Siavash H. Khajavi, Guangkai Jiang
  26. Detoxifying Large Language Models via Autoregressive Reward Guided Representation Editing ↗Yisong Xiao, Aishan Liu, Siyuan Liang et al.
  27. DevFD : Developmental Face Forgery Detection by Learning Shared and Orthogonal LoRA Subspaces ↗Tianshuo Zhang, Li Gao, Siran Peng et al.
  28. DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control ↗Oleksii Furman, Ulvi Movsum-zada, Patryk Marszałek et al.
  29. DiEP: Adaptive Mixture-of-Experts Compression through Differentiable Expert Pruning ↗Sikai Bai, H. J. Li, Jie Zhang et al.
  30. Diff-ICMH: Harmonizing Machine and Human Vision in Image Compression with Generative Prior ↗Ruoyu Feng, Yunpeng Qi, Jinming Liu et al.
  31. DiffBreak: Is Diffusion-Based Purification Robust? ↗Andre Kassis, Urs Hengartner, Yaoliang Yu
  32. DiffLiG: Diffusion-enhanced Liquid Graph with Attention Propagation for Grid-to-Station Precipitation Correction ↗Yuxiang Li, Yang Zhang, Li Li et al.
  33. Differentiable Constraint-Based Causal Discovery ↗Jincheng Zhou, Mengbo Wang, Anqi He et al.
  34. Differentiable Cyclic Causal Discovery Under Unmeasured Confounders ↗Muralikrishnna G. Sethuraman, Faramarz Fekri
  35. Differentiable Decision Tree via "ReLU+Argmin" Reformulation ↗Qiangqiang Mao, Jiayang Ren, Yixiu Wang et al.
  36. Differentiable Generalized Sliced Wasserstein Plans ↗Laëtitia Chapel, Romain Tavenard, Samuel Vaiter
  37. Differentiable Hierarchical Visual Tokenization ↗Marius Aasan, Martine Hjelkrem-Tan, Nico Catalano et al.
  38. Differentiable Structure Learning and Causal Discovery for General Binary Data ↗Chang Deng, Bryon Aragam
  39. Differentiable extensions with rounding guarantees for combinatorial optimization over permutations ↗Robert R. Nerem, Zhishang Luo, Akbar Rafiey et al.
  40. Differential Privacy for Euclidean Jordan Algebra with Applications to Private Symmetric Cone Programming ↗Zhao Song, Jianfei Xue, Lichen Zhang
  41. Differential Privacy on Fully Dynamic Streams ↗Yuan Ying Qiu, Ke Yi
  42. Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates ↗Andrew M. Lowy, Daogao Liu
  43. Differentially Private Gomory-Hu Trees ↗Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard et al.
  44. Differentially Private High-dimensional Variable Selection via Integer Programming ↗Petros Prastakos, Kayhan Behdin, Rahul Mazumder
  45. Differentially Private Quantiles with Smaller Error ↗Jacob Imola, Fabrizio Boninsegna, Hannah Keller et al.
  46. Differentially Private Relational Learning with Entity-level Privacy Guarantees ↗Yinan Huang, Haoteng Yin, Eli Chien et al.
  47. Diffusion Federated Dataset ↗SEOKJU HAHN, Junghye Lee
  48. Diffusion Generative Modeling on Lie Group Representations ↗Marco Bertolini, Tuan Le, Djork-Arné Clevert
  49. Diffusion Guided Adversarial State Perturbations in Reinforcement Learning ↗Xiaolin Sun, Feidi Liu, Zhengming Ding et al.
  50. Diffusion Models Meet Contextual Bandits ↗Imad Aouali
  51. Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive ↗Tyler Farghly, Peter Potaptchik, Samuel Howard et al.
  52. Diffusion Network Inference for Cross-layer Cascades ↗Siyu Huang, Yubai Yuan, Abdul Basit Adeel
  53. Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification ↗Ziming Ye, Minshuo Chen
  54. Diffusion on Demand: Selective Caching and Modulation for Efficient Generation ↗Hee Min Choi, Hyoa Kang, Dokwan Oh et al.
  55. Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL ↗Ruitao Wu, Yifan Zhao, Guangyao Chen et al.
  56. Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation ↗Jeongin Kim, Wonho Bae, YouLee Han et al.
  57. Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis ↗Hengyuan Cao, Yutong Feng, Biao Gong et al.
  58. Dimension-adapted Momentum Outscales SGD ↗Damien Ferbach, Katie Everett, Gauthier Gidel et al.
  59. Dimension-free Score Matching and Time Bootstrapping for Diffusion Models ↗Syamantak Kumar, Anant Raj, Purnamrita Sarkar
  60. Dimensional Collapse in VQVAEs: Evidence and Remedies ↗Jiayou Zhang, Yifan Shen, Guangyi Chen et al.
  61. Dimensionality Mismatch Between Brains and Artificial Neural Networks ↗Santiago Galella, Maren H. Wehrheim, Matthias Kaschube
  62. Direct Fisher Score Estimation for Likelihood Maximization ↗Sherman Khoo, Yakun Wang, Song Liu et al.
  63. Directed-Tokens: A Robust Multi-Modality Alignment Approach to Large Language-Vision Models ↗Thanh-Dat Truong, Huu-Thien Tran, Trần Thái Sơn et al.
  64. DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization ↗Gang Li, Ming C. Lin, Tomer Galanti et al.
  65. Discovering Compositional Hallucinations in LVLMs ↗Sibei Yang, Ge Zheng, Jiajin Tang et al.
  66. Discovering Data Structures: Nearest Neighbor Search and Beyond ↗Omar Salemohamed, Laurent Charlin, Shivam Garg et al.
  67. Discovering Latent Graphs with GFlowNets for Diverse Conditional Image Generation ↗Bailey Trang, Parham Saremi, Alan Wang et al.
  68. Discovering Opinion Intervals from Conflicts in Signed Graphs ↗Peter Blohm, Florian Chen, Aristides Gionis et al.
  69. Discovering Symbolic Partial Differential Equation by Abductive Learning ↗En-Hao Gao, Cunjing Ge, Yuan Jiang et al.
  70. Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees ↗Yuchen Liang, Yingbin Liang, Lifeng Lai et al.
  71. Discrete Neural Flow Samplers with Locally Equivariant Transformer ↗Zijing Ou, Ruixiang Zhang, Yingzhen Li
  72. Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling ↗Javier E. Santos, Agnese Marcato, Roman Colman et al.
  73. Discretization-free Multicalibration through Loss Minimization over Tree Ensembles ↗Hongyi Jin, Zijun Ding, Dung Daniel Ngo et al.
  74. Disentangled Representation Learning via Modular Compositional Bias ↗Whie Jung, Dong Hoon Lee, Seunghoon Hong
  75. Disentanglement Beyond Static vs. Dynamic: A Benchmark and Evaluation Framework for Multi-Factor Sequential Representations ↗Tal Barami, Nimrod Berman, Ilan Naiman et al.
  76. Disentangling Hyperedges through the Lens of Category Theory ↗Yoonho Lee, Junseok Lee, Sang Won Seo et al.
  77. Disentangling Latent Shifts of In-Context Learning with Weak Supervision ↗Josip Jukić, Jan Šnajder
  78. Disentangling misreporting from genuine adaptation in strategic settings: a causal approach ↗Dylan Zapzalka, Trenton Chang, Lindsay Warrenburg et al.
  79. Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search ↗Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou et al.
  80. Distances for Markov chains from sample streams ↗Sergio Calo, Anders Jönsson, Gergely Neu et al.
  81. Distil-E2D: Distilling Image-to-Depth Priors for Event-Based Monocular Depth Estimation ↗Jie Long Lee, Gim Hee Lee
  82. Distilling LLM Prior to Flow Model for Generalizable Agent’s Imagination in Object Goal Navigation ↗Badi Li, Ren-Jie Lu, Yu Zhou et al.
  83. Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences? ↗Paul Gölz, Nika Haghtalab, Kunhe Yang
  84. Distributed Multi-Agent Bandits Over Erdős-Rényi Random Networks ↗Jingyuan Liu, Hao Qiu, Lin Yang et al.
  85. Distributed mediation analysis with communication efficiency ↗Shaomin Li
  86. Distribution Learning Meets Graph Structure Sampling ↗Arnab Bhattacharyya, Sutanu Gayen, Philips George John et al.
  87. Distribution-Aligned Decoding for Efficient LLM Task Adaptation ↗Senkang Hu, Xudong Han, Jinqi Jiang et al.
  88. Distribution-Aware Tensor Decomposition for Compression of Convolutional Neural Networks ↗Alper Kalle, Théo Rudkiewicz, Mohamed Ouerfelli et al.
  89. Distributional Adversarial Attacks and Training in Deep Hedging ↗Guangyi He, Tobias Sutter, Lukas Gonon
  90. Distributional Autoencoders Know the Score ↗Andrej Leban
  91. Distributional LLM-as-a-Judge ↗Luyu Chen, Zeyu Zhang, Haoran Tan et al.
  92. Distributional Training Data Attribution: What do Influence Functions Sample? ↗Bruno Mlodozeniec, Isaac Reid, Sam Power et al.
  93. Distributionally Robust Feature Selection ↗Maitreyi Swaroop, Tamar Krishnamurti, Bryan Wilder
  94. Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values ↗Hadi Hosseini, Samarth Khanna
  95. Diverse Influence Component Analysis: A Geometric Approach to Nonlinear Mixture Identifiability ↗Hoang Son Nguyen, Xiao Fu
  96. Diversifying Parallel Ergodic Search: A Signature Kernel Evolution Strategy ↗Sreevardhan Sirigiri, Christian Hughes, Ian Abraham et al.
  97. Diversity Is All You Need for Contrastive Learning: Spectral Bounds on Gradient Magnitudes ↗Peter Juma Ochieng
  98. Diversity-oriented Deep Multi-modal Clustering ↗Yanzheng Wang, Xin Yang, Yujun Wang et al.
  99. Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness ↗Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu et al.
  100. Do LVLMs Truly Understand Video Anomalies? Revealing Hallucination via Co-Occurrence Patterns ↗Menghao Zhang, Huazheng Wang, Pengfei Ren et al.

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