Search Results - coding ((algorithmics OR (algorithm OR Algorithms)) OR (algorithmsssic OR algorithmsssic))

Power Battery Detection by Zhao, Xiaoqi, Cao, Peiqian, Yu, Chenyang, Feng, Zonglei, Zhang, Lihe, Liu, Hanqi, Zuo, Jiaming, Pang, Youwei, Ouyang, Jinsong, Lin, Weisi, Fakhri, Georges El, Lu, Huchuan, Liu, Xiaofeng

Table of Contents: “… algorithms struggle with densely packed plates, low contrast, scale variation, and imaging artifacts…”
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Adaptive Confidence-Wise Loss for Improved Lens Structure Segmentation in AS-OCT by Xiao, Zunjie, Wu, Xiao, Liu, Tianhang, Hu, Lingxi, Zhang, Yinling, Zhang, Xiaoqing, Higashita, Risa, Liu, Jiang

Table of Contents: “… threshold optimization algorithm to adjust the confidence threshold of ACW dynamically. Additionally…”
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ST-Raptor: LLM-Powered Semi-Structured Table Question Answering by Tang, Zirui, Niu, Boyu, Zhou, Xuanhe, Li, Boxiu, Zhou, Wei, Wang, Jiannan, Li, Guoliang, Zhang, Xinyi, Wu, Fan

Table of Contents: “… with an effective algorithm for constructing the tree. Second, we define a set of basic tree operations to guide…”
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Dual-Thresholded Heatmap-Guided Proposal Clustering and Negative Certainty Supervision with Enhanced Base Network for Weakly Supervised Object Detection by Guo, Yuelin, He, Haoyu, Chen, Zhiyuan, Huang, Zitong, Lu, Renhao, Shi, Lu, Wang, Zejun, Zhang, Weizhe

Table of Contents: “… selector (HGPS) algorithm, which utilizes dual thresholds on heatmaps to pre-select proposals, enabling…”
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Machine Learning for Quantum Noise Reduction by Kendre, Karan

Table of Contents: “… mitigation essential for practical quantum computation. While traditional quantum error correction codes…”
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Language Models that Think, Chat Better by Bhaskar, Adithya, Ye, Xi, Chen, Danqi

Table of Contents: “… rule-based rewards in verifiable domains such as mathematics and code. However, RLVR leads to limited…”
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Active Attacks: Red-teaming LLMs via Adaptive Environments by Yun, Taeyoung, St-Charles, Pierre-Luc, Park, Jinkyoo, Bengio, Yoshua, Kim, Minsu

Table of Contents: “… exploration, we introduce \textit{Active Attacks}, a novel RL-based red-teaming algorithm that adapts its…”
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From Static to Dynamic: Adaptive Monte Carlo Search for Mathematical Process Supervision by Ma, Jie, Qi, Shihao, Xing, Rui, Yin, Ziang, Wei, Bifan, Liu, Jun, Liu, Tongliang

Table of Contents: “…, it enhances the path expansion through a Monte Carlo algorithm with a temporally adaptive policy that begins…”
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Vision-Zero: Scalable VLM Self-Improvement via Strategic Gamified Self-Play by Wang, Qinsi, Liu, Bo, Zhou, Tianyi, Shi, Jing, Lin, Yueqian, Chen, Yiran, Li, Hai Helen, Wan, Kun, Zhao, Wentian

Table of Contents: “…-SPO), a novel training algorithm that alternates between Self-Play and reinforcement learning…”
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FOLK: Fast Open-Vocabulary 3D Instance Segmentation via Label-guided Knowledge Distillation by Wu, Hongrui, Gao, Zhicheng, Cao, Jin, Yao, Kelu, Shen, Wen, Wei, Zhihua

Table of Contents: “… propose a label-guided distillation algorithm to distill open-vocabulary knowledge from label-consistent 2…”
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Probabilistic Hyper-Graphs using Multiple Randomly Masked Autoencoders for Semi-supervised Multi-modal Multi-task Learning by Mihai-Cristian, Pîrvu, Leordeanu, Marius

Table of Contents: “… the distribution of hyper-edges on each forward pass. Additionally, the model adapts the standard MAE algorithm…”
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FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models by Liu, Junkang, Shang, Fanhua, Liu, Hongying, Tian, Yuxuan, Liu, Yuanyuan, Liu, Jin, Zhu, Kewen, Lin, Zhouchen

Table of Contents: “… \underline{AdamW} algorithm, called \texttt{FedAdamW}, for training and fine-tuning various large models…”
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MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping by Huang, Yushi, Wang, Zining, Yuan, Zhihang, Ding, Yifu, Gong, Ruihao, Guo, Jinyang, Liu, Xianglong, Zhang, Jun

Table of Contents: “… the optimal thresholds, we introduce a frontier search algorithm that exploits monotonicity properties…”
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Solving Spatial Supersensing Without Spatial Supersensing by Udandarao, Vishaal, Karthik, Shyamgopal, Nath, Surabhi S., Hochlehnert, Andreas, Bethge, Matthias, Prabhu, Ameya

Table of Contents: “… object-count predictions unchanged; instead, Cambrian-S inference algorithm relies largely on a shortcut…”
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Spira: Exploiting Voxel Data Structural Properties for Efficient Sparse Convolution in Point Cloud Networks by Adamopoulos, Dionysios, Poulopoulou, Anastasia, Goumas, Georgios, Giannoula, Christina

Table of Contents: “… for GPUs. Spira proposes (i) a high-performance one-shot search algorithm that builds the kernel map…”
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MICCAI STS 2024 Challenge: Semi-Supervised Instance-Level Tooth Segmentation in Panoramic X-ray and CBCT Images by Wang, Yaqi, Li, Zhi, Wu, Chengyu, Liu, Jun, Zhang, Yifan, Ni, Jiaxue, Luo, Qian, Chen, Jialuo, Zhang, Hongyuan, Liu, Jin, Han, Can, Fu, Kaiwen, Ji, Changkai, Cai, Xinxu, Hao, Jing, Zheng, Zhihao, Xu, Shi, Chen, Junqiang, Zhang, Qianni, Qian, Dahong, Wang, Shuai, Zhou, Huiyu

Table of Contents: “…) registered teams. To ensure algorithmic excellence and full transparency, we rigorously evaluated the valid…”
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Semantic Soft Bootstrapping: Long Context Reasoning in LLMs without Reinforcement Learning by Mitra, Purbesh, Ulukus, Sennur

Table of Contents: “… optimization (GRPO), which is a commonly used RLVR algorithm. Our code is available at https://github.com…”
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How Far are Modern Trackers from UAV-Anti-UAV? A Million-Scale Benchmark and New Baseline by Zhang, Chunhui, Liu, Li, Zhang, Zhipeng, Wang, Yong, Wen, Hao, Zhou, Xi, Ge, Shiming, Wang, Yanfeng

Table of Contents: “… of 50 modern deep tracking algorithms demonstrates that there is still significant room for improvement…”
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TraPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning by Yang, Shenzhi, Zhu, Guangcheng, Zheng, Xing, MA, Yingfan, Chen, Zhongqi, Song, Bowen, Wang, Weiqiang, Zhao, Junbo, Chen, Gang, Wang, Haobo

Table of Contents: “… an effective policy optimization algorithm, TraPO, that identifies reliable unlabeled samples by matching…”
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HERO-Sign: Hierarchical Tuning and Efficient Compiler-Time GPU Optimizations for SPHINCS+ Signature Generation by Zhou, Yaoyun, Wang, Qian

Table of Contents: “… algorithm that adapts fusion schemes to different GPU architectures. To further improve performance, HERO…”
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