Paper

  • CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data

    Nakamasa Inoue, Motoaki Kawanabe, Fumiya Kitamori, Shuhei Kurita, Jungdae Lee, Taiki Miyanishi p77758-77770 from Advances in Neural Information Processing Systems 36
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  • CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation

    Yan-Pei Cao, Handi Chen, Peng Dai, Weipeng Deng, Xiaojuan Qi, Ying Shan, Xiuzhe Wu, Yang Wu p34426-34438 from Advances in Neural Information Processing Systems 36
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  • CLadder: Assessing Causal Reasoning in Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CLadder: Assessing Causal Reasoning in Language Models

    Kevin Blin, Yuen Chen, Fernando Gonzalez Adauto, Luigi Gresele, Zhijing Jin, Ojasv Kamal, Max Kleiman-Weiner, Felix Leeb, Zhiheng Lyu, Mrinmaya Sachan, Bernhard Schölkopf p31038-31065 from Advances in Neural Information Processing Systems 36
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  • CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models

    Dong Gong, Saurav Jha, Lina Yao p129146-129186 from Advances in Neural Information Processing Systems 37
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  • CLARIFYING TERMINOLOGY FOR ASSESSING CIRCULARITY IN TIMBER CONSTRUCTION

    World Conference on Timber Engineering 2025

    CLARIFYING TERMINOLOGY FOR ASSESSING CIRCULARITY IN TIMBER CONSTRUCTION

    Marieke Stritzke, Sandra Schuster p594-601 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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  • ClashEval: Quantifying the tug-of-war between an LLM’s internal prior and external evidence

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ClashEval: Quantifying the tug-of-war between an LLM’s internal prior and external evidence

    Eric Wu, Kevin Wu, James Zou p33402-33422 from Advances in Neural Information Processing Systems 37
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  • Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations

    Yuval Benjamini, Yuli Slavutsky p89213-89248 from Advances in Neural Information Processing Systems 37
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  • Class-Aware Adversarial Transformers for Medical Image Segmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Class-Aware Adversarial Transformers for Medical Image Segmentation

    Sandeep Chinchali, Siyuan Dong, James Duncan, Fenglin Liu, Lawrence Staib, Ufuk Topcu, Chenyu You, Ruihan Zhao p29582-29596 from Advances in Neural Information Processing Systems 35
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  • Class-Conditional Conformal Prediction with Many Classes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Class-Conditional Conformal Prediction with Many Classes

    Anastasios Angelopoulos, Stephen Bates, Tiffany Ding, Michael Jordan, Ryan Tibshirani p64555-64576 from Advances in Neural Information Processing Systems 36
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  • Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization

    De Cheng, Yuxuan Du, Xinbo Gao, Bo Han, Tongliang Liu, Yixiong Ning, Nannan Wang, Heng Yang p11104-11116 from Advances in Neural Information Processing Systems 35
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  • Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning

    Sheng-Jun Huang, Hao-Zhe Liu, Gang Niu, Masashi Sugiyama, Jiahao Xiao, Ming-Kun Xie p25731-25747 from Advances in Neural Information Processing Systems 36
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  • Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification

    Yuankai Luo, Lei Shi, Xiao-Ming Wu p97650-97669 from Advances in Neural Information Processing Systems 37
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