Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals

Tam Nguyen, Tan Nguyen, Richard Baraniuk p80233-80256 from Advances in Neural Information Processing Systems 36

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Mitigating Overthinking in Large Reasoning Models via Manifold Steering

Yao Huang, Huanran Chen, Shouwei Ruan, Yichi Zhang, Xingxing Wei, Yinpeng Dong p113645-113670 from Advances in Neural Information Processing Systems 38

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy

Cameron Allen, Aaron Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott, Nicholas Petrocelli, Omer Gottesman, Ronald Parr, Michael Littman, George Konidaris p62988-63028 from Advances in Neural Information Processing Systems 37

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Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling

Nguyen Phuc, Ngoc-Hieu Nguyen, Duy M. H. Nguyen, Anji Liu, An Mai, Thanh Binh Nguyen, Daniel Sonntag, Khoa D Doan p110259-110283 from Advances in Neural Information Processing Systems 38

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation

Xiaoying Zhang, Jean-François Ton, Wei Shen, Hongning Wang, Yang Liu p81717-81747 from Advances in Neural Information Processing Systems 37

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Mitigating Semantic Collapse in Partially Relevant Video Retrieval

WonJun Moon, MinSeok Jung, Gilhan Park, Tae-Young Kim, Cheol-Ho Cho, Woojin Jun, Jae-Pil Heo p26288-26309 from Advances in Neural Information Processing Systems 38

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Mitigating Sexual Content Generation via Embedding Distortion in Text-conditioned Diffusion Models

Jaesin Ahn, Heechul Jung p141-176 from Advances in Neural Information Processing Systems 38

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mitigating Source Bias for Fairer Weak Supervision

Changho Shin, Sonia Cromp, Dyah Adila, Frederic Sala p33564-33605 from Advances in Neural Information Processing Systems 36

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mitigating Spurious Correlations via Disagreement Probability

Hyeonggeun Han, Sehwan Kim, Hyungjun Joo, Sangwoo Hong, Jungwoo Lee p74363-74382 from Advances in Neural Information Processing Systems 37

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Mitigating Spurious Features in Contrastive Learning with Spectral Regularization

Naghmeh Ghanooni, Waleed Mustafa, Dennis Wagner, Sophie Fellenz, Anthony Lin, Marius Kloft p119412-119444 from Advances in Neural Information Processing Systems 38

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Mitigating Test-Time Bias for Fair Image Retrieval

Fanjie Kong, Shuai Yuan, Weituo Hao, Ricardo Henao p71520-71539 from Advances in Neural Information Processing Systems 36

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Mitigating the Effect of Incidental Correlations on Part-based Learning

Gaurav Bhatt, Deepayan Das, Leonid Sigal, Vineeth N Balasubramanian p63738-63757 from Advances in Neural Information Processing Systems 36

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Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective

Yifei Zhang, Hao Zhu, Yankai Chen, Zixing Song, Piotr Koniusz, Irwin King p67533-67550 from Advances in Neural Information Processing Systems 36

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Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy

Xiang Li, Chendi Wang, Buxin Su, Qi Long, Weijie Su p186788-186824 from Advances in Neural Information Processing Systems 38

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Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models

Xiyuan Zhang, Danielle Maddix Robinson, Junming Yin, Nick Erickson, Abdul Fatir Ansari, Boran Han, Shuai Zhang, Leman Akoglu, Christos Faloutsos, Michael Mahoney, Tony Hu, Huzefa Rangwala, George Karypis, Yuyang (Bernie) Wang p17831-17876 from Advances in Neural Information Processing Systems 38

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Mix and Reason: Reasoning Over Semantic Topology with Data Mixing for Domain Generalization

Chaoqi Chen, Luyao Tang, Feng Liu, Gangming Zhao, Yue Huang, Yizhou Yu p33302-33315 from Advances in Neural Information Processing Systems 35

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Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging

Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Ziyu Zhao, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang p124703-124732 from Advances in Neural Information Processing Systems 38

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Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models

Yuchao Gu, Xintao Wang, Jay Zhangjie Wu, Yujun Shi, Yunpeng Chen, Zihan Fan, Wuyou Xiao, Rui Zhao, Shuning Chang, Weijia Wu, Yixiao Ge, Ying Shan, Mike Zheng Shou p15890-15902 from Advances in Neural Information Processing Systems 36

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MIX: A Multi-view Time-Frequency Interactive Explanation Framework for Time Series Classification

Viet-Hung Tran, Ngoc Phu Doan, Zichi Zhang, Tuan Pham, Phi Hung Nguyen, Xuan Nguyen, Hans Vandierendonck, Ira Assent, Thai Son Mai p54897-54942 from Advances in Neural Information Processing Systems 38

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MixAT: Combining Continuous and Discrete Adversarial Training for LLMs

Csaba Dékány, Stefan Balauca, Dimitar I. Dimitrov, Robin Staab, Martin Vechev p96436-96469 from Advances in Neural Information Processing Systems 38

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Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes

Zhenfeng Tu, Santiago Aranguri, Arthur Jacot p106059-106104 from Advances in Neural Information Processing Systems 37

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Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation

Dapeng Hu, Jian Liang, Jun Hao Liew, Chuhui Xue, Song Bai, Xinchao Wang p37923-37941 from Advances in Neural Information Processing Systems 36

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Mixed-Initiative Multiagent Apprenticeship Learning for Human Training of Robot Teams

Esmaeil Seraj, Jerry Xiong, Mariah Schrum, Matthew Gombolay p35426-35440 from Advances in Neural Information Processing Systems 36

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning

Yuyang Deng, Samory Kpotufe p103117-103154 from Advances in Neural Information Processing Systems 38

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Neural Information Processing Systems Foundation, Inc. (NeurIPS)

Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals

Mitigating Overthinking in Large Reasoning Models via Manifold Steering

Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy

Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling

Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation

Mitigating Semantic Collapse in Partially Relevant Video Retrieval

Mitigating Sexual Content Generation via Embedding Distortion in Text-conditioned Diffusion Models

Mitigating Source Bias for Fairer Weak Supervision

Mitigating Spurious Correlations via Disagreement Probability

Mitigating Spurious Features in Contrastive Learning with Spectral Regularization

Mitigating Test-Time Bias for Fair Image Retrieval

Mitigating the Effect of Incidental Correlations on Part-based Learning

Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective

Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy

Mitra: Mixed Synthetic Priors for Enhancing Tabular Foundation Models

Mix and Reason: Reasoning Over Semantic Topology with Data Mixing for Domain Generalization

Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging

Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models

MIX: A Multi-view Time-Frequency Interactive Explanation Framework for Time Series Classification

MixAT: Combining Continuous and Discrete Adversarial Training for LLMs

Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes

Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation

Mixed-Initiative Multiagent Apprenticeship Learning for Human Training of Robot Teams

Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning

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