ICLR

2022–2026 LIVE

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Machine Learning

2026 · 5,351 papers

このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。

2026 · ICLR
DisTaC: Conditioning Task Vectors via Distillation for Robust Model Merging
Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryotaro Shimizu, Ioannis Mitliagkas, Hiroki Naganuma
Machine Learning
日本大学: 東京科学大学 / 京都大学
2026 · ICLR
Discern Truth from Falsehood: Reducing Over-Refusal via Contrastive Refinement
Yuxiao Lu, Lin Xu, yang sun, Wenjun Li, Jie Shi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disco: Densely-overlapping Cell Instance Segmentation via Adjacency-aware Collaborative Coloring
Rui Sun, Yiwen Yang, Kaiyu Guo, Chen Jiang, Dongli Xu, Zhaonan Liu, Tan Pan, LIMEI HAN, Xue Jiang, Wu Wei, Yuan Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DiscoX: Benchmarking Discourse-Level Translation in Expert Domains
Xiying ZHAO, Zhoufutu Wen, Zhixuan Chen, Jingzhe Ding, Jianpeng Jiao, Shuai Li, Xi Li, Danni Liang, Shengda Long, Qianqian Liu, Xianbo Wu, Hongwan Gao, Xiang Gao, LIANG HU, Jiashuo Liu, Liumengyun, Weiran Shi, Chenghao Yang, Qianyu Yang, Xuanliang Zhang, Ge Zhang, Wenhao Huang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discount Model Search for Quality Diversity Optimization in High-Dimensional Measure Spaces
Bryon Tjanaka, Henry Chen, Matthew Fontaine, Stefanos Nikolaidis
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discounted Online Convex Optimization: Uniform Regret Across a Continuous Interval
Wenhao Yang, Sifan Yang, Lijun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discovering Novel LLM Experts via Task-Capability Coevolution
Andrew Dai, Boris Meinardus, Ciaran Regan, Yingtao Tian, Yujin Tang
Machine Learning
日本大学: 筑波大学
2026 · ICLR
Discovering alternative solutions beyond the simplicity bias in recurrent neural networks
William Qian, Cengiz Pehlevan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discovering and Steering Interpretable Concepts in Large Generative Music Models
Nikhil Singh, Manuel Cherep, Pattie Maes
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discovering heterogeneous synaptic plasticity rules via large-scale neural evolution
Ziyuan Ye, Beichen Huang, Yujie Wu, Guozhang Chen, Jibin Wu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Adjoint Matching
Oswin So, Brian Karrer, Chuchu Fan, Ricky T. Q. Chen, Guan-Horng Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Bayesian Sample Inference for Graph Generation
Ole Petersen, Marcel Kollovieh, Marten Lienen, Stephan Günnemann
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
Marco Jiralerspong, Esther Derman, Danilo Vucetic, Nikolay Malkin, Bilun Sun, Tianyu Zhang, Pierre-Luc Bacon, Gauthier Gidel
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Diffusion Trajectory Alignment via Stepwise Decomposition
Jiaqi Han, Austin Wang, Minkai Xu, Wenda Chu, Meihua Dang, Haotian Ye, Huayu Chen, Yisong Yue, Stefano Ermon
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Diffusion for Bundle Construction
Teng Tu, Ai Li, Yunshan Ma, Shuo Xu, Xiaohao Liu, Haokai Ma, Liang Pang, Tat-Seng Chua
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving
Pengxiang Li, Yinan Zheng, Yue Wang, Huimin Wang, Hang Zhao, Jingjing Liu, Xianyuan Zhan, Kun Zhan, XianPeng Lang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching
Zhengyan Wan, Yidong Ouyang, Liyan Xie, Fang Fang, Hongyuan Zha, Guang Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Latent Features Ablate Adversarial Attack: A Robust Prompt Tuning Framework for VLMs
YANG CHEN, Yanbin Wei, James Kwok, Yu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Discrete Variational Autoencoding via Policy Search
Michael Drolet, Firas Al-Hafez, Aditya Bhatt, Jan Peters, Oleg Arenz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangled Hierarchical VAE for 3D Human-Human Interaction Generation
Zichen Geng, Zeeshan Hayder, Bo Miao, Jian Liu, Wei Liu, Ajmal Mian
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangled Representation Learning for Parametric Partial Differential Equations
Ning Liu, Lu Zhang, Tian Gao, Yue Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangled Robot Learning via Separate Forward and Inverse Dynamics Pretraining
Wenyao Zhang, Bozhou Zhang, Zekun Qi, Wenjun Zeng, Xin Jin, Li Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangled representation learning through unsupervised symmetry group discovery
Barthélémy Dang-Nhu, Louis Annabi, Sylvain ARGENTIERI
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentanglement of Variations with Multimodal Generative Modeling
Yijie Zhang, Yiyang Shen, Weiran Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangling Knowledge Representations for Large Language Model Editing
Mengqi Zhang, Zisheng Zhou, Xiaotian Ye, Qiang Liu, Zhaochun Ren, Zhumin Chen, Pengjie Ren
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangling Length Bias in Preference Learning via Response-Conditioned Modeling
Jianfeng Cai, Jinhua Zhu, Ruopei Sun, Yue Wang, Li, Wengang Zhou, Houqiang Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disentangling the Factors of Convergence between Brains and DINOv3
Joséphine Raugel, Marc Szafraniec, Huy Vo, camille couprie, Jérémy Rapin, Stéphane d'Ascoli, Patrick Labatut, Piotr Bojanowski, Valentin Wyart, Jean-Remi King
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DispViT: Direct Stereo Disparity Regression with a Single-Stream Vision Transformer
Tongfan Guan, Jiaxin Guo, Tianyu Huang, Jinhu Dong, Chen Wang, Yun-Hui Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
Idan Pipano, Shoham Sabach, Kavosh Asadi, Mohammad Ghavamzadeh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Disrupting Hierarchical Reasoning: Adversarial Protection for Geographic Privacy in Multimodal Reasoning Models
Jiaming Zhang, CHE WANG, Yang Cao, Longtao Huang, Wei Yang Bryan Lim
Machine Learning
日本大学: 東京科学大学
2026 · ICLR
Dissecting Representation Misalignment in Contrastive Learning via Influence Function
Huanyi Xie, Chenyang Ren, Khouloud Saadi, Shu Yang, Zhen Tan, Jingfeng Zhang, Lijie Hu, Di Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DistDF: Time-series Forecasting Needs Joint-distribution Wasserstein Alignment
Hao Wang, Licheng Pan, Yuan Lu, Zhixuan Chu, Xiaoxi Li, Shuting He, Zi Chan, Qingsong Wen, Haoxuan Li, Zhouchen Lin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials
Kevin Han, Bowen Deng, Amir Barati Farimani, Gerbrand Ceder
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DistillKac: Few-Step Image Generation via Damped Wave Equations
Weiqiao Han, Chenlin Meng, Christopher Manning, Stefano Ermon
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distillation of Large Language Models via Concrete Score Matching
Yeongmin Kim, Donghyeok Shin, Mina Kang, Byeonghu Na, Il-chul Moon
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distilled Pretraining: A modern lens of Data, In-Context Learning and Test-Time Scaling
Sachin Goyal, David Lopez-Paz, Kartik Ahuja
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distilling Causal Signals for One-Shot Directed Evolution of Antibodies
Sai Pooja Mahajan, Natasa Tagasovska, Stefania Vasilaki, Arian Jamasb, Andrew Watkins, Rajesh Ranganath
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
Alana Deng, Sugitha Janarthanan, Yan Sun, Zihao Jing, Pingzhao Hu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distilling the Thought, Watermarking the Answer: A Principle Semantic Guided Watermark for Reasoning Large Language Models
Shuliang Liu, Xingyu Li, Hongyi Liu, Dong Fang, Bingchen Duan, Zheng Qi, Lingfeng Su, Xuming Hu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distilling to Hybrid Attention Models via KL-Guided Layer Selection
Yanhong Li, Songlin Yang, Shawn Tan, Mayank Mishra, Rameswar Panda, Jiawei Zhou, Yoon Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distractor-free Generalizable 3D Gaussian Splatting
Yanqi Bao, Jing Liao, Jing Huo, Yang Gao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributed Algorithms for Euclidean Clustering
Vincent Cohen-Addad, Liudeng Wang, David Woodruff, Samson Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distribution-Aware Multi-Granularity Phase Coding: Towards Lower Conversion Error for Spike-Driven Large Language Models
Hanyuan Zheng, Haozhen Zhang, Tianshuo Chen, Zhaogeng Liu, Yi Chang, Bin Gu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distribution-informed Online Conformal Prediction
Dongjian Hu, Junxi Wu, Shu-Tao Xia, Changliang Zou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributional Consistency Loss: Beyond Pointwise Data Terms in Inverse Problems
George Webber, Andrew Reader
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning
Haoyue Dai, Immanuel Albrecht, Peter Spirtes, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributional Machine Unlearning via Selective Data Removal
Youssef Allouah, Rachid Guerraoui, Sanmi Koyejo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence
Wenzhe Yin, Zehao Xiao, Pan Zhou, Shujian Yu, Jiayi Shen, Jan-jakob Sonke, Efstratios Gavves
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributional value gradients for stochastic environments
Baptiste Debes, Tinne Tuytelaars
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation
Seonghwi Kim, Sungho Jo, Wooseok Ha, Minwoo Chae
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization
Chengrui (Ray) Qu, Christopher Yeh, Kishan Panaganti, Eric Mazumdar, Adam Wierman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributionally Robust Linear Regression with Block Lewis Weights
Naren Sarayu Manoj, Kumar Kshitij Patel
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributionally Robust Optimization via Generative Ambiguity Modeling
Jiaqi Wen, Jianyi Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Distributions as Actions: A Unified Framework for Diverse Action Spaces
Jiamin He, A. Rupam Mahmood, Martha White
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Divergence-Free Neural Networks with Application to Image Denoising
Sébastien Herbreteau, Etienne Meunier
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diverse Dictionary Learning
Yujia Zheng, Zijian Li, Shunxing Fan, Andrew Gordon Wilson, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diverse Text Decoding via Iterative Reweighting
Ruiqi Shi, Sinno Jialin Pan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diverse Text-to-Image Generation via Contrastive Noise Optimization
Byungjun Kim, Soobin Um, Jong Chul YE
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diverse and Sparse Mixture-of-Experts for Causal Subgraph–Based Out-of-Distribution Graph Learning
Jerry Sun, Mohamed Abubakr Hassan, Yaoyu Zhang, Wanying Zhang, Chi-Guhn Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diversified Multinomial Logit Contextual Bandits
Heesang Ann, Taehyun Hwang, Min-hwan Oh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diversity-Enhanced Reasoning for Subjective Questions
Yumeng Wang, Zhiyuan Fan, Jiayu Liu, Jen-Tse Huang, Yi R. Fung
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Diversity-Incentivized Exploration for Versatile Reasoning
Zican Hu, Shilin Zhang, Yafu Li, Jianhao (Elliott) Yan, Xuyang Hu, Leyang Cui, Xiaoye Qu, Chunlin Chen, Yu Cheng, Zhi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Divid: Disentangled Spatial-Temporal Modeling within LLMs for Temporally Grounded Video Understanding
Yepeng Tang, Weining Wang, Longteng Guo, Tongtian Yue, Wenxuan Wang, Chunjie Zhang, Jing Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Divide and Abstract: Autoformalization via Decomposition and Abstraction Learning
Marcus Min, Yeqi Gao, Wilson Sy, Zhaoyu Li, Xujie Si, Osbert Bastani
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Divide, Harmonize, Then Conquer It: Shooting Multi-Commodity Flow Problems with Multimodal Language Models
Xinyu Yuan, Yan Qiao, Zonghui Wang, Wenzhi CHEN
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do 3D Large Language Models Really Understand 3D Spatial Relationships?
Xianzheng Ma, Tao Sun, Shuai Chen, Yash Bhalgat, Jindong Gu, Angel Chang, Iro Armeni, Iro Laina, Songyou Peng, Victor Prisacariu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do LLM Agents Know How to Ground, Recover, and Assess? Evaluating Epistemic Competence in Information-Seeking Agents
Jiaqi Shao, Yuxiang Lin, Munish P Lohani, Yufeng Miao, Bing Luo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do LLMs Forget What They Should? Evaluating In-Context Forgetting in Large Language Models
Yuli Qian, Zechuan Yang, Wenbiao Ding, Hongzhi Li, Yutao Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do Large Language Models Know What They Are Capable Of?
Casey Barkan, Sidney Black, Oliver Sourbut
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs
Zhihe Yang, Xufang Luo, Zilong Wang, Dongqi Han, Zhiyuan He, Dongsheng Li, Yunjian Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do Vision-Language Models Respect Contextual Integrity in Location Disclosure?
Ruixin Yang, Ethan Mendes, Arthur Wang, James Hays, Sauvik Das, Wei Xu, Alan Ritter
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models
Dang Nguyen, Jiping Li, Jinghao Zheng, Baharan Mirzasoleiman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Do We Really Need Permutations? Impact of Model Width on Linear Mode Connectivity
Akira Ito, Masanori Yamada, Daiki Chijiwa, Atsutoshi Kumagai
Machine Learning
日本大学: 東北大学
2026 · ICLR
DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
Dongze Wu, Feng Qiu, Yao Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
Ming Ma, Jue Zhang, Fangkai Yang, Yu Kang, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning
Yung Hwei Lai, Kaiming Liu, Ziyue Wang, Weizhi Ma, Yang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Does FLUX Already Know How to Perform Physically Plausible Image Composition?
Shilin Lu, Zhuming Lian, Zihan Zhou, Shaocong Zhang, Chen Zhao, Adams Kong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Does Higher Interpretability Imply Better Utility? A Pairwise Analysis on Sparse Autoencoders
Xu Wang, Yan Hu, Wang Benyou, Difan Zou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Does Weak-to-strong Generalization Happen under Spurious Correlations?
Chenruo Liu, Yijun Dong, Qi Lei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Does the Data Processing Inequality Reflect Practice? On the Utility of Low-Level Tasks
Roy Turgeman, Tom Tirer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?
Ku Onoda, Paavo Parmas, Manato Yaguchi, Yutaka Matsuo
Machine Learning
日本大学: 東京大学
2026 · ICLR
Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation
Changxi Chi, Jun Xia, Yufei Huang, Zhuoli Ouyang, Cheng Tan, Yunfan Liu, Jingbo Zhou, Chang Yu, Liangyu Yuan, Siyuan Li, Zelin Zang, Stan Z Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Domain Expansion: A Latent Space Construction Framework for Multi-Task Learning
Chi-Yao Huang, Khoa Vo, Aayush Verma, Duo Lu, Yezhou Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Don't Just Fine-tune the Agent, Tune the Environment
Siyuan Lu, Zechuan Wang, Hongxuan Zhang, Qintong Wu, Leilei Gan, Chenyi Zhuang, Jinjie Gu, Tao Lin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models
Zemin Huang, Yuhang Wang, Zhiyang Chen, Guo-Jun Qi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Don't Shift the Trigger: Robust Gradient Ascent for Backdoor Unlearning
Xingyi Zhao, Tian Xie, Xiaojun Qi, Depeng Xu, Shuhan Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Don't Throw Away Your Beams: Improving Consistency-based Uncertainties in LLMs via Beam Search
Ekaterina Fadeeva, Maiya Goloburda, Aleksandr Rubashevskii, Roman Vashurin, Artem Shelmanov, Preslav Nakov, Mrinmaya Sachan, Maxim Panov
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Don't Throw Away Your Pretrained Model
Shangbin Feng, Wenhao Yu, Yike Wang, Hongming Zhang, Yulia Tsvetkov, Dong Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Don’t Pass@k: A Bayesian Framework for Large Language Model Evaluation
Mohsen Hariri, Amirhossein Samandar, Michael Hinczewski, Vipin Chaudhary
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Doubly-Regressing Approach for Subgroup Fairness
Kunwoong Kim, Kyungseon Lee, Jihu Lee, Dongyoon Yang, Yongdai Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Doubly-Robust LLM-as-a-Judge: Externally Valid Estimation with Imperfect Personas
Luke Guerdan, Justin Whitehouse, Kimberly Truong, Ken Holstein, Steven Wu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning
Yicheng Lang, Yihua Zhang, Chongyu Fan, Changsheng Wang, Jinghan Jia, Sijia Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Doxing via the Lens: Revealing Location-related Privacy Leakage on Multi-modal Large Reasoning Models
Weidi Luo, Tianyu Lu, Qiming Zhang, Xiaogeng Liu, Bin Hu, Yue Zhao, Jieyu Zhao, Song Gao, Patrick McDaniel, Zhen Xiang, Chaowei Xiao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Dr.LLM: Dynamic Layer Routing in LLMs
Ahmed Heakl, Martin Gubri, Salman Khan, Sangdoo Yun, Seong Joon Oh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DrVoice: Parallel Speech-Text Voice Conversation Model via Dual-Resolution Speech Representations
Chao-Hong Tan, Qian Chen, Wen Wang, Chong Deng, Qinglin Zhang, Luyao Cheng, Hai Yu, Xin Zhang, Xiang Lyu, Tianyu Zhao, Chong Zhang, Yukun Ma, Yafeng Chen, Hui Wang, Jiaqing Liu, Xiangang Li, Jieping Ye
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Draft-based Approximate Inference for LLMs
Kevin Galim, Ethan Ewer, Wonjun Kang, Minjae Lee, Hyung Koo, Kangwook Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DragFlow: Unleashing DiT Priors with Region-Based Supervision for Drag Editing
Zihan Zhou, Shilin Lu, Shuli Leng, Shaocong Zhang, Zhuming Lian, Xinlei Yu, Adams Kong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Dragging with Geometry: From Pixels to Geometry-Guided Image Editing
Xinyu Pu, Hongsong Wang, Jie Gui, Pan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing
Ziyun Zeng, David Junhao Zhang, Wei Li, Mike Zheng Shou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
DreamCS: Geometry-Aware Text-to-3D Generation with Unpaired 3D Reward Supervision
Xiandong Zou, Ruihao Xia, Hongsong Wang, Pan Zhou
Machine Learning
日本大学: 関与なし（対象大学）