Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward

    Daejin Jo, Sungwoong Kim, Daniel Nam, Taehwan Kwon, Seungeun Rho, Jongmin Kim, Donghoon Lee p30432-30445 from Advances in Neural Information Processing Systems 35
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  • LeDex: Training LLMs to Better Self-Debug and Explain Code

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LeDex: Training LLMs to Better Self-Debug and Explain Code

    Nan Jiang, Xiaopeng Li, Shiqi Wang, Qiang Zhou, Soneya Hossain, Baishakhi Ray, Varun Kumar, Xiaofei Ma, Anoop Deoras p35517-35543 from Advances in Neural Information Processing Systems 37
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  • LEDiT: Your Length-Extrapolatable Diffusion Transformer without Positional Encoding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LEDiT: Your Length-Extrapolatable Diffusion Transformer without Positional Encoding

    Shen Zhang, Siyuan Liang, Yaning Tan, Zhaowei Chen, Linze Li, Ge Wu, Yuhao Chen, Shuheng Li, Zhenyu Zhao, Caihua Chen, Jiajun Liang, Yao Tang p25787-25820 from Advances in Neural Information Processing Systems 38
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  • Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-Based Best-First Search for Sokoban Planning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-Based Best-First Search for Sokoban Planning

    Dieqiao Feng, Carla Gomes, Bart Selman p36295-36307 from Advances in Neural Information Processing Systems 35
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  • LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

    Neel Guha, Julian Nyarko, Daniel Ho, Christopher Ré, Adam Chilton, Aditya K, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel Rockmore, Diego Zambrano, Dmitry Talisman, Enam Hoque, Faiz Surani, Frank Fagan, Galit Sarfaty, et al. p44123-44279 from Advances in Neural Information Processing Systems 36
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  • LeMiCa: Lexicographic Minimax Path Caching for Efficient Diffusion-Based Video Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LeMiCa: Lexicographic Minimax Path Caching for Efficient Diffusion-Based Video Generation

    Huanlin Gao, Ping Chen, Fuyuan Shi, Chao Tan, Zhaoxiang Liu, Fang Zhao, Kai Wang, Shiguo Lian p146703-146730 from Advances in Neural Information Processing Systems 38
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  • Lending Interaction Wings to Recommender Systems with Conversational Agents

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Lending Interaction Wings to Recommender Systems with Conversational Agents

    Jiarui Jin, Xianyu Chen, Fanghua Ye, Mengyue Yang, Yue Feng, Weinan Zhang, Yong Yu, Jun Wang p27951-27979 from Advances in Neural Information Processing Systems 36
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  • Length Generalization via Auxiliary Tasks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Length Generalization via Auxiliary Tasks

    Pranjal Awasthi, Anupam Gupta, Ravi Kumar p98765-98787 from Advances in Neural Information Processing Systems 38
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  • Length Optimization in Conformal Prediction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Length Optimization in Conformal Prediction

    Shayan Kiyani, George Pappas, Hamed Hassani p99519-99563 from Advances in Neural Information Processing Systems 37
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  • LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction

    Di Liu, Anastasis Stathopoulos, Qilong Zhangli, Yunhe Gao, Dimitris Metaxas p54187-54198 from Advances in Neural Information Processing Systems 36
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  • Less but More: Linear Adaptive Graph Learning Empowering Spatiotemporal Forecasting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less but More: Linear Adaptive Graph Learning Empowering Spatiotemporal Forecasting

    Jiaming Ma, Binwu Wang, Guanjun Wang, Kuo Yang, Zhengyang Zhou, Pengkun Wang, Xu Wang, Yang Wang p65101-65137 from Advances in Neural Information Processing Systems 38
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  • Less Greedy Equivalence Search

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less Greedy Equivalence Search

    Adiba Ejaz, Elias Bareinboim p136463-136504 from Advances in Neural Information Processing Systems 38
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  • Less Is More, but Where? Dynamic Token Compression via LLM-Guided Keyframe Prior

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less Is More, but Where? Dynamic Token Compression via LLM-Guided Keyframe Prior

    Yulin Li, Haokun GUI, Ziyang Fan, Junjie Wang, Bin Kang, BIN CHEN, Zhuotao Tian p174158-174201 from Advances in Neural Information Processing Systems 38
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  • Less is More: an Attention-free Sequence Prediction Modeling for Offline Embodied Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less is More: an Attention-free Sequence Prediction Modeling for Offline Embodied Learning

    Wei Huang, Jianshu Zhang, Leiyu Wang, Heyue Li, Luoyi Fan, Yichen Zhu, Nanyang Ye, Qinying Gu p2958-2987 from Advances in Neural Information Processing Systems 38
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  • Less is More: Improving LLM Alignment via Preference Data Selection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less is More: Improving LLM Alignment via Preference Data Selection

    Xun Deng, Han Zhong, Rui Ai, Fuli Feng, Zheng Wang, Xiangnan He p179024-179050 from Advances in Neural Information Processing Systems 38
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  • Less is More: Local Intrinsic Dimensions of Contextual Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less is More: Local Intrinsic Dimensions of Contextual Language Models

    Benjamin Matthias Ruppik, Julius von Rohrscheidt, Carel van Niekerk, Michael Heck, Renato Vukovic, Shutong Feng, Hsien-chin Lin, Nurul Lubis, Bastian Rieck, Marcus Zibrowius, Milica Gasic p75559-75592 from Advances in Neural Information Processing Systems 38
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  • Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning

    Lifan Zhao, Yanyan Shen, Zhaoyang Liu, xue wang, Jiaji Deng p190344-190369 from Advances in Neural Information Processing Systems 38
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  • Less-Forgetting Multi-Lingual Fine-Tuning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Less-Forgetting Multi-Lingual Fine-Tuning

    Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang, Lu Chen, Yunjun Gao p14917-14928 from Advances in Neural Information Processing Systems 35
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  • LESS: Label-Efficient and Single-Stage Referring 3D Segmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    LESS: Label-Efficient and Single-Stage Referring 3D Segmentation

    Xuexun Liu, Xiaoxu Xu, Jinlong Li, Qiudan Zhang, Xu Wang, Nicu Sebe, Lin Ma p11164-11185 from Advances in Neural Information Processing Systems 37
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  • Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve

    Yuanzhe Liu, Ryan Deng, Tim Kaler, Xuhao Chen, Charles Leiserson, Yao Ma, Jie Chen p120859-120915 from Advances in Neural Information Processing Systems 38
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  • Let a Neural Network be Your Invariant

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Let a Neural Network be Your Invariant

    Mirco Giacobbe, Daniel Kroening, Abhinandan Pal, Michael Tautschnig p83183-83210 from Advances in Neural Information Processing Systems 38
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  • Let Brain Rhythm Shape Machine Intelligence for Connecting Dots on Graphs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Let Brain Rhythm Shape Machine Intelligence for Connecting Dots on Graphs

    Jiaqi Ding, Tingting Dan, Zhixuan Zhou, Guorong Wu p13143-13165 from Advances in Neural Information Processing Systems 38
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  • Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis

    Xu Yan, Heshen Zhan, Chaoda Zheng, Jiantao Gao, Ruimao Zhang, Shuguang Cui, Zhen Li p32398-32411 from Advances in Neural Information Processing Systems 35
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  • Let LRMs Break Free from Overthinking via Self-Braking Tuning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Let LRMs Break Free from Overthinking via Self-Braking Tuning

    Haoran Zhao, Yuchen Yan, Yongliang Shen, Haolei Xu, Wenqi Zhang, Kaitao Song, Jian Shao, Weiming Lu, Jun Xiao, Yueting Zhuang p2138-2164 from Advances in Neural Information Processing Systems 38
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