Extrapolation-Directed Crossover for Job-shop Scheduling Problems: Complementary Combination with JOX. - Jun Sakuma; Shigenobu Kobayashi (GECCO, 2000)

Extrapolation-directed crossover for real-coded GA: overcoming deceptive phenomena by extrapolative search. - Jun Sakuma; Shigenobu Kobayashi (CEC, 2001)

k-tablet Structures and Crossover on Latent Variables for Real-Coded GA. - Jun Sakuma; Shigenobu Kobayashi (GECCO Late Breaking Papers, 2002)

Adaptive isolation model using data clustering for multimodal function optimization. - Shin Ando; Jun Sakuma; Shigenobu Kobayashi (GECCO, 2005)

Real-coded crossover as a role of kernel density estimation. - Jun Sakuma; Shigenobu Kobayashi (GECCO, 2005)

Latent variable crossover for k-tablet structures and its application to lens design problems. - Jun Sakuma; Shigenobu Kobayashi (GECCO, 2005)

Fast Approximate Similarity Search in Extremely High-Dimensional Data Sets. - Michael E. Houle; Jun Sakuma (ICDE, 2005)

An Effective Rule Based Policy Representation and its Optimization using Inter Normal Distribution Crossover. - Chikao Tsuchiya; Jun Sakuma; Isao Ono; Shigenobu Kobayashi (WSTST, 2005)

Instance-Based Policy Search using Binomial Distribution Crossover and Iterated Refreshment. - Chikao Tsuchiya; Kokolo Ikeda; Jun Sakuma; Isao Ono; Shigenobu Kobayashi (IEEE Congress on Evolutionary Computation, 2006)

Local search for multiobjective function optimization: pareto descent method. - Ken Harada; Jun Sakuma; Shigenobu Kobayashi (GECCO, 2006)

An Evolutionary Algorithm for Optimizing Functions with UV Structures. - Hiroshi Takeichi; Isao Ono; Jun Sakuma; Shigenobu Kobayashi (SMC, 2006)

Constraint-Handling Method for Multi-objective Function Optimization: Pareto Descent Repair Operator. - Ken Harada; Jun Sakuma; Isao Ono; Shigenobu Kobayashi (EMO, 2007)

Uniform sampling of local pareto-optimal solution curves by pareto path following and its applications in multi-objective GA. - Ken Harada; Jun Sakuma; Shigenobu Kobayashi; Isao Ono (GECCO, 2007)

A genetic algorithm for privacy preserving combinatorial optimization. - Jun Sakuma; Shigenobu Kobayashi (GECCO, 2007)

Functionally specialized CMA-ES: a modification of CMA-ES based on the specialization of the functions of covariance matrix adaptation and step size adaptation. - Youhei Akimoto; Jun Sakuma; Isao Ono; Shigenobu Kobayashi (GECCO, 2008)

Privacy-preserving reinforcement learning. - Jun Sakuma; Shigenobu Kobayashi; Rebecca N. Wright (ICML, 2008)

Large-Scale k-Means Clustering with User-Centric Privacy Preservation. - Jun Sakuma; Shigenobu Kobayashi (PAKDD, 2008)

Functional-Specialization Multi-Objective Real-Coded Genetic Algorithm: FS-MOGA. - Naoki Hamada; Jun Sakuma; Shigenobu Kobayashi; Isao Ono (PPSN, 2008)

Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection. - Jun Sakuma; Rebecca N. Wright (ACML, 2009)

A new real-coded genetic algorithm using the adaptive selection network for detecting multiple optima. - Dan Oshima; Atsushi Miyamae; Jun Sakuma; Shigenobu Kobayashi; Isao Ono (IEEE Congress on Evolutionary Computation, 2009)

Adaptation of expansion rate for real-coded crossovers. - Youhei Akimoto; Jun Sakuma; Isao Ono; Shigenobu Kobayashi (GECCO, 2009)

Link analysis for private weighted graphs. - Jun Sakuma; Shigenobu Kobayashi (SIGIR, 2009)

Online Prediction with Privacy. - Jun Sakuma; Hiromi Arai (ICML, 2010)

Collusion-resistant privacy-preserving data mining. - Bin Yang; Hiroshi Nakagawa; Issei Sato; Jun Sakuma (KDD, 2010)

Large-scale k-means clustering with user-centric privacy-preservation. - Jun Sakuma; Shigenobu Kobayashi (Knowl. Inf. Syst., 2010)

Fairness-aware Learning through Regularization Approach. - Toshihiro Kamishima; Shotaro Akaho; Jun Sakuma (ICDM Workshops, 2011)

Privacy Preserving Semi-supervised Learning for Labeled Graphs. - Hiromi Arai; Jun Sakuma (ECML/PKDD (1), 2011)

Considerations on Fairness-Aware Data Mining. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (ICDM Workshops, 2012)

Fairness-Aware Classifier with Prejudice Remover Regularizer. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (ECML/PKDD (2), 2012)

Enhancement of the Neutrality in Recommendation. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (Decisions@RecSys, 2012)

Applicability of existing anonymization methods to large location history data in urban travel. - Rie Shigetomi Yamaguchi; Keiichi Hirota; Koki Hamada; Katsumi Takahashi; Kazutaka Matsuzaki; Jun Sakuma; Yasuyuki Shirai (SMC, 2012)

The Independence of Fairness-Aware Classifiers. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (ICDM Workshops, 2013)

Privacy-Preserving Protocol for Epidemiology in Effect of Radiation. - Hiroaki Kikuchi; Tomoki Sato; Jun Sakuma (IMIS, 2013)

Round-Efficient Private Stable Matching from Additive Homomorphic Encryption. - Tadanori Teruya; Jun Sakuma (ISC, 2013)

Efficiency Improvement of Neutrality-Enhanced Recommendation. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (Decisions@RecSys, 2013)

Privacy-Preserving Hypothesis Testing for the Analysis of Epidemiological Medical Data. - Hiroaki Kikuchi; Tomoki Sato; Jun Sakuma (AINA, 2014)

A scheme for privacy-preserving ontology mapping. - Toshiyuki Amagasa; Fan Zhang; Jun Sakuma; Hiroyuki Kitagawa (IDEAS, 2014)

Privacy-Preserving Dose-Response Relationship Test. - Hiroaki Kikuchi; Tomoki Sato; Jun Sakuma (NBiS, 2014)

Neutralized Empirical Risk Minimization with Generalization Neutrality Bound. - Kazuto Fukuchi; Jun Sakuma (ECML/PKDD (1), 2014)

Correcting Popularity Bias by Enhancing Recommendation Neutrality. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (RecSys Posters, 2014)

Oblivious Evaluation of Non-deterministic Finite Automata with Application to Privacy-Preserving Virus Genome Detection. - Hirohito Sasakawa; Hiroki Harada; David duVerle; Hiroki Arimura; Koji Tsuda; Jun Sakuma (WPES, 2014)

Bloom Filter Bootstrap: Privacy-Preserving Estimation of the Size of an Intersection. - Hiroaki Kikuchi; Jun Sakuma (J. Inf. Process., 2014)

Differentially Private Analysis of Outliers. - Rina Okada; Kazuto Fukuchi; Jun Sakuma (ECML/PKDD (2), 2015)

Efficient Secure Outsourcing of Genome-Wide Association Studies. - Wenjie Lu; Yoshiji Yamada; Jun Sakuma (IEEE Symposium on Security and Privacy Workshops, 2015)

Privacy-Preserving Statistical Analysis by Exact Logistic Regression. - David A. duVerle; Shohei Kawasaki; Yoshiji Yamada; Jun Sakuma; Koji Tsuda (IEEE Symposium on Security and Privacy Workshops, 2015)

Fairness-Aware Learning with Restriction of Universal Dependency using f-Divergences. - Kazuto Fukuchi; Jun Sakuma (CoRR, 2015)

Differentially Private Analysis of Outliers. - Rina Okada; Kazuto Fukuchi; Kazuya Kakizaki; Jun Sakuma (CoRR, 2015)

Prediction with Model-Based Neutrality. - Kazuto Fukuchi; Toshihiro Kamishima; Jun Sakuma (IEICE Trans. Inf. Syst., 2015)

Privacy-preserving search for chemical compound databases. - Kana Shimizu; Koji Nuida; Hiromi Arai; Shigeo Mitsunari; Nuttapong Attrapadung; Michiaki Hamada; Koji Tsuda; Takatsugu Hirokawa; Jun Sakuma; Goichiro Hanaoka; Kiyoshi Asai (BMC Bioinform., 2015)

Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption. - Wenjie Lu; Yoshiji Yamada; Jun Sakuma (BMC Medical Informatics Decis. Mak., 2015)

Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization. - Toshiyuki Takada; Hiroyuki Hanada; Yoshiji Yamada; Jun Sakuma; Ichiro Takeuchi (ACML, 2016)

Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization. - Hiroaki Kikuchi; Takayasu Yamaguchi; Koki Hamada; Yuji Yamaoka; Hidenobu Oguri; Jun Sakuma (AINA, 2016)

A Study from the Data Anonymization Competition Pwscup 2015. - Hiroaki Kikuchi; Takayasu Yamaguchi; Koki Hamada; Yuji Yamaoka; Hidenobu Oguri; Jun Sakuma (DPM/QASA@ESORICS, 2016)

Fairy ring: Ubiquitous secure multiparty computation framework for smartphone applications. - Tadanori Teruya; Yoshiki Aoki; Jun Sakuma (ISITA, 2016)

Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization. - Hiroyuki Hanada; Atsushi Shibagaki; Jun Sakuma; Ichiro Takeuchi (CoRR, 2016)

Using Fully Homomorphic Encryption for Statistical Analysis of Categorical, Ordinal and Numerical Data. - Wenjie Lu; Shohei Kawasaki; Jun Sakuma (IACR Cryptol. ePrint Arch., 2016)

Mis-operation Resistant Searchable Homomorphic Encryption. - Keita Emura; Takuya Hayashi 001; Noboru Kunihiro; Jun Sakuma (AsiaCCS, 2017)

Privacy-preserving and Optimal Interval Release for Disease Susceptibility. - Kosuke Kusano; Ichiro Takeuchi; Jun Sakuma (AsiaCCS, 2017)

Malware Analysis of Imaged Binary Samples by Convolutional Neural Network with Attention Mechanism. - Hiromu Yakura; Shinnosuke Shinozaki; Reon Nishimura; Yoshihiro Oyama; Jun Sakuma (AISec@CCS, 2017)

Towards Privacy-Preserving Record Linkage with Record-Wise Linkage Policy. - Takahito Kaiho; Wenjie Lu; Toshiyuki Amagasa; Jun Sakuma (DEXA (1), 2017)

Differentially Private Empirical Risk Minimization with Input Perturbation. - Kazuto Fukuchi; Quang Khai Tran; Jun Sakuma (DS, 2017)

Differentially Private Chi-squared Test by Unit Circle Mechanism. - Kazuya Kakizaki; Kazuto Fukuchi; Jun Sakuma (ICML, 2017)

Minimax optimal estimators for additive scalar functionals of discrete distributions. - Kazuto Fukuchi; Jun Sakuma (ISIT, 2017)

Differentially Private Semi-Supervised Classification. - Xu Long; Jun Sakuma (SMARTCOMP, 2017)

Efficiently Monitoring Small Data Modification Effect for Large-Scale Learning in Changing Environment. - Hiroyuki Hanada; Atsushi Shibagaki; Jun Sakuma; Ichiro Takeuchi (AAAI, 2018)

More Practical Privacy-Preserving Machine Learning as A Service via Efficient Secure Matrix Multiplication. - Wenjie Lu; Jun Sakuma (WAHC@CCS, 2018)

Non-interactive and Output Expressive Private Comparison from Homomorphic Encryption. - Wenjie Lu; Jun-Jie Zhou; Jun Sakuma (AsiaCCS, 2018)

Recommendation Independence. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (FAT, 2018)

Minimax Optimal Additive Functional Estimation with Discrete Distribution: Slow Divergence Speed Case. - Kazuto Fukuchi; Jun Sakuma (ISIT, 2018)

Outsourced Private Function Evaluation with Privacy Policy Enforcement. - Noboru Kunihiro; Wenjie Lu; Takashi Nishide; Jun Sakuma (TrustCom/BigDataSE, 2018)

Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values. - Hiroyuki Hanada; Toshiyuki Takada; Jun Sakuma; Ichiro Takeuchi (CoRR, 2018)

Minimax Optimal Additive Functional Estimation with Discrete Distribution. - Kazuto Fukuchi; Jun Sakuma (CoRR, 2018)

General-to-Detailed GAN for Infrequent Class Medical Images. - Tatsuki Koga; Naoki Nonaka; Jun Sakuma; Jun Seita (CoRR, 2018)

Model-based and actual independence for fairness-aware classification. - Toshihiro Kamishima; Shotaro Akaho; Hideki Asoh; Jun Sakuma (Data Min. Knowl. Discov., 2018)

Study on Record Linkage of Anonymizied Data. - Hiroaki Kikuchi; Takayasu Yamaguchi; Koki Hamada; Yuji Yamaoka; Hidenobu Oguri; Jun Sakuma (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018)

Toward Distribution Estimation under Local Differential Privacy with Small Samples. - Takao Murakami; Hideitsu Hino; Jun Sakuma (Proc. Priv. Enhancing Technol., 2018)

Recommendation with k-Anonymized Ratings. - Jun Sakuma; Tatsuya Osame (Trans. Data Priv., 2018)

Robust Watermarking of Neural Network with Exponential Weighting. - Ryota Namba; Jun Sakuma (AsiaCCS, 2019)

Robust Audio Adversarial Example for a Physical Attack. - Hiromu Yakura; Jun Sakuma (IJCAI, 2019)

Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs. - Thien Q. Tran; Jun Sakuma (KDD, 2019)

Neural malware analysis with attention mechanism. - Hiromu Yakura; Shinnosuke Shinozaki; Reon Nishimura; Yoshihiro Oyama; Jun Sakuma (Comput. Secur., 2019)

Locally Differentially Private Minimum Finding. - Kazuto Fukuchi; Chia-Mu Yu; Arashi Haishima; Jun Sakuma (CoRR, 2019)

Generate (Non-Software) Bugs to Fool Classifiers. - Hiromu Yakura; Youhei Akimoto; Jun Sakuma (AAAI, 2020)

Deep generative model for non-convex constraint handling. - Naoki Sakamoto; Eiji Semmatsu; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (GECCO, 2020)

Seasonal-adjustment Based Feature Selection Method for Large-scale Search Engine Logs. - Thien Q. Tran; Jun Sakuma (CoRR, 2020)

AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment. - Rei Sato; Jun Sakuma; Youhei Akimoto (AAAI, 2021)

Toward Practical Adversarial Attacks on Face Verification Systems. - Kazuya Kakizaki; Taiki Miyagawa; Inderjeet Singh; Jun Sakuma (BIOSIG, 2021)

Adaptive scenario subset selection for min-max black-box continuous optimization. - Atsuhiro Miyagi; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (GECCO, 2021)

Convergence rate of the (1+1)-evolution strategy with success-based step-size adaptation on convex quadratic functions. - Daiki Morinaga; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (GECCO, 2021)

Level generation for angry birds with sequential VAE and latent variable evolution. - Takumi Tanabe; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (GECCO, 2021)

Application of Adversarial Examples to Physical ECG Signals. - Taiga Ono; Takeshi Sugawara 001; Jun Sakuma; Tatsuya Mori (CoRR, 2021)

Unsupervised Causal Binary Concepts Discovery with VAE for Black-Box Model Explanation. - Thien Q. Tran; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (AAAI, 2022)

Black-box min-max continuous optimization using CMA-ES with worst-case ranking approximation. - Atsuhiro Miyagi; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (GECCO, 2022)

Did You Use My GAN to Generate Fake? Post-hoc Attribution of GAN Generated Images via Latent Recovery. - Syou Hirofumi; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (IJCNN, 2022)

Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning. - Rei Sato; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (IJCNN, 2022)

Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis. - Yuwei Sun; Hideya Ochiai; Jun Sakuma (IJCNN, 2022)

Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification. - Takumi Tanabe; Rei Sato; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (NeurIPS, 2022)

Explicitly Constrained Black-Box Optimization With Disconnected Feasible Domains Using Deep Generative Models. - Naoki Sakamoto; Rei Sato; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (IEEE Access, 2022)

Domain Generalization via Adversarially Learned Novel Domains. - Yu Zhe; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (IEEE Access, 2022)

Convergence rate of the (1+1)-evolution strategy on locally strongly convex functions with lipschitz continuous gradient and their monotonic transformations. - Daiki Morinaga; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (CoRR, 2022)

Locally Differentially Private Minimum Finding. - Kazuto Fukuchi; Chia-Mu Yu; Jun Sakuma (IEICE Trans. Inf. Syst., 2022)

Heterogeneous Domain Adaptation with Positive and Unlabeled Data. - Junki Mori; Ryo Furukawa 003; Isamu Teranishi; Jun Sakuma (IEEE Big Data, 2023)

Privformer: Privacy-preserving Transformer with MPC. - Yoshimasa Akimoto; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (EuroS&P, 2023)

Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs. - Kaiwen Xu; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (IJCAI, 2023)

Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping. - Joshua Butke; Noriaki Hashimoto; Ichiro Takeuchi; Hiroaki Miyoshi; Koichi Ohshima; Jun Sakuma (MLMI@MICCAI (2), 2023)

Demographic Parity Constrained Minimax Optimal Regression under Linear Model. - Kazuto Fukuchi; Jun Sakuma (NeurIPS, 2023)

Certified Defense for Content Based Image Retrieval. - Kazuya Kakizaki; Kazuto Fukuchi; Jun Sakuma (WACV, 2023)

Unauthorized AI cannot recognize me: Reversible adversarial example. - Jiayang Liu; Weiming Zhang 001; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (Pattern Recognit., 2023)

Adaptive scenario subset selection for worst-case optimization and its application to well placement optimization. - Atsuhiro Miyagi; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (Appl. Soft Comput., 2023)

CAMRI Loss: Improving the Recall of a Specific Class without Sacrificing Accuracy. - Daiki Nishiyama; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (IEICE Trans. Inf. Syst., 2023)

Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min-Max Optimization and Its Application to Berthing Control Tasks. - Atsuhiro Miyagi; Yoshiki Miyauchi; Atsuo Maki; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (ACM Trans. Evol. Learn. Optim., 2023)

Statistically Significant Pattern Mining With Ordinal Utility. - Thien Q. Tran; Kazuto Fukuchi; Youhei Akimoto; Jun Sakuma (IEEE Trans. Knowl. Data Eng., 2023)

Trojan attribute inference attack on gradient boosting decision trees. - Kunihiro Ito; Batnyam Enkhtaivan; Isamu Teranishi; Jun Sakuma (EuroS&P, 2024)

Linear Convergence Rate Analysis of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions. - Daiki Morinaga; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (GECCO Companion, 2024)

Instance-Level Trojan Attacks on Visual Question Answering via Adversarial Learning in Neuron Activation Space. - Yuwei Sun; Hideya Ochiai; Jun Sakuma (IJCNN, 2024)

Remembering Transformer for Continual Learning. - Yuwei Sun; Ippei Fujisawa; Arthur Juliani; Jun Sakuma; Ryota Kanai (CoRR, 2024)

Adversarial Attacks on Hidden Tasks in Multi-Task Learning. - Yu Zhe; Rei Nagaike; Daiki Nishiyama; Kazuto Fukuchi; Jun Sakuma (CoRR, 2024)

Behavior-Targeted Attack on Reinforcement Learning with Limited Access to Victim's Policy. - Shojiro Yamabe; Kazuto Fukuchi; Ryoma Senda; Jun Sakuma (CoRR, 2024)

Zero-shot domain adaptation based on dual-level mix and contrast. - Yu Zhe; Jun Sakuma (CoRR, 2024)

Parameter Matching Attack: Enhancing Practical Applicability of Availability Attacks. - Yu Zhe; Jun Sakuma (CoRR, 2024)

Attacking-Distance-Aware Attack: Semi-targeted Model Poisoning on Federated Learning. - Yuwei Sun; Hideya Ochiai; Jun Sakuma (IEEE Trans. Artif. Intell., 2024)

Convergence Rate of the (1+1)-ES on Locally Strongly Convex and Lipschitz Smooth Functions. - Daiki Morinaga; Kazuto Fukuchi; Jun Sakuma; Youhei Akimoto (IEEE Trans. Evol. Comput., 2024)

Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift. - Mitsuhiro Fujikawa; Youhei Akimoto; Jun Sakuma; Kazuto Fukuchi (AISTATS, 2025)

Deterministic and Probabilistic Certified Defenses for Content-Based Image Retrieval. - Kazuya Kakizaki; Kazuto Fukuchi; Jun Sakuma (IEICE Trans. Inf. Syst., 2025)

BADTV: Unveiling Backdoor Threats in Third-Party Task Vectors. - Chia-Yi Hsu; Yu-Lin Tsai; Yu Zhe; Yan-Lun Chen; Chih-Hsun Lin; Chia-Mu Yu; Yang Zhang; Chun-Ying Huang; Jun Sakuma (CoRR, 2025)

Explainable Classifier for Malignant Lymphoma Subtyping via Cell Graph and Image Fusion. - Daiki Nishiyama; Hiroaki Miyoshi; Noriaki Hashimoto; Koichi Ohshima; Hidekata Hontani; Ichiro Takeuchi; Jun Sakuma (CoRR, 2025)

Data Poisoning Attacks to Locally Differentially Private Range Query Protocols. - Ting-Wei Liao; Chih-Hsun Lin; Yu-Lin Tsai; Takao Murakami; Chia-Mu Yu; Jun Sakuma; Chun-Ying Huang; Hiroaki Kikuchi (CoRR, 2025)

Disrupting Model Merging: A Parameter-Level Defense Without Sacrificing Accuracy. - Junhao Wei; Yu Zhe; Jun Sakuma (CoRR, 2025)