Search Results - decoding (Algorithmssic OR algorithm)

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  1. 1701

    The weight hierarchy of decreasing norm-trace codes by Camps-Moreno, Eduardo, López, Hiram H., Matthews, Gretchen L., San-José, Rodrigo

    Published 2024
    Table of Contents: “… of type II, $t$-resilient functions, bounding the cardinality of the output in list decoding algorithms…”
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  2. 1702
  3. 1703

    Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning by Park, Sungjin, Liu, Xiao, Gong, Yeyun, Choi, Edward

    Published 2024
    Table of Contents: “… reasoning benchmarks demonstrate that our approach outperforms both single language model decoding…”
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  4. 1704

    HashEvict: A Pre-Attention KV Cache Eviction Strategy using Locality-Sensitive Hashing by Liu, Minghui, Rabbani, Tahseen, O'Halloran, Tony, Sankaralingam, Ananth, Hartley, Mary-Anne, Huang, Furong, Fermüller, Cornelia, Aloimonos, Yiannis

    Published 2024
    Table of Contents: “… significant GPU memory. In this work, we introduce HashEvict, an algorithm that uses locality-sensitive…”
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  5. 1705

    Shifting-Merging: Secure, High-Capacity and Efficient Steganography via Large Language Models by Bai, Minhao, Yang, Jinshuai, Pang, Kaiyi, Huang, Yongfeng, Gao, Yue

    Published 2025
    Table of Contents: “… of ShiMer, we design a reordering algorithm to minimize the occurrence of interval splitting during decoding…”
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  6. 1706
  7. 1707

    Masked Generative Nested Transformers with Decode Time Scaling by Goyal, Sahil, Tula, Debapriya, Jain, Gagan, Shenoy, Pradeep, Jain, Prateek, Paul, Sujoy

    Published 2025
    Table of Contents: “… computational efficiency. Most of these algorithms involve multiple passes over a transformer model to generate…”
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  8. 1708

    IG-MCTS: Human-in-the-Loop Cooperative Navigation under Incomplete Information by Chen, Shenghui, Zhao, Ruihan, Chinchali, Sandeep, Topcu, Ufuk

    Published 2025
    Table of Contents: “… Information Gain Monte Carlo Tree Search (IG-MCTS), an online planning algorithm that jointly optimizes…”
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  9. 1709

    Uplink OFDM Channel Prediction with Hybrid CNN-LSTM for 6G Non-Terrestrial Networks by De Filippo, Bruno, Amatetti, Carla, Vanelli-Coralli, Alessandro

    Published 2025
    Table of Contents: “… response (CFR) matrix in absence of pilots. The algorithm employs an encoder-decoder convolutional neural…”
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  10. 1710

    Exploring Contextual Attribute Density in Referring Expression Counting by Wang, Zhicheng, Pan, Zhiyu, Peng, Zhan, Cheng, Jian, Xiao, Liwen, Jiang, Wei, Cao, Zhiguo

    Published 2025
    Table of Contents: “…Referring expression counting (REC) algorithms are for more flexible and interactive counting…”
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  11. 1711

    SINR: Sparsity Driven Compressed Implicit Neural Representations by Jayasundara, Dhananjaya, Rajagopalan, Sudarshan, Ranasinghe, Yasiru, Tran, Trac D., Patel, Vishal M.

    Published 2025
    Table of Contents: “… coding schemes employed. In this paper, we introduce SINR, an innovative compression algorithm…”
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  12. 1712

    Decoding the mechanisms of the Hattrick football manager game using Bayesian network structure learning by Constantinou, Anthony C., Higgins, Nicholas, Kitson, Neville K.

    Published 2025
    Table of Contents: “…. Hattrick's game-engine mechanics are partially hidden, and users have attempted to decode them…”
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  13. 1713

    Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models by Liu, Yi, Liu, Dianqing, Zhu, Mingye, Guo, Junbo, Zhang, Yongdong, Mao, Zhendong

    Published 2025
    Table of Contents: “… algorithm with iterative token-level decoding to address the common first-token latency issue in comparable…”
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  14. 1714

    Mamba Drafters for Speculative Decoding by Choi, Daewon, Oh, Seunghyuk, Dingliwal, Saket, Tack, Jihoon, Kim, Kyuyoung, Song, Woomin, Kim, Seojin, Han, Insu, Shin, Jinwoo, Galstyan, Aram, Katiyar, Shubham, Bodapati, Sravan Babu

    Published 2025
    Table of Contents: “…Speculative decoding has emerged as a promising approach to accelerating large language model (LLM…”
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  15. 1715

    Leveraging erasure errors in logical qubits with metastable $^{171}$Yb atoms by Zhang, Bichen, Liu, Genyue, Bornet, Guillaume, Horvath, Sebastian P., Peng, Pai, Ma, Shuo, Huang, Shilin, Puri, Shruti, Thompson, Jeff D.

    Published 2025
    Table of Contents: “…Implementing large-scale quantum algorithms with practical advantage will require fault-tolerance…”
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  16. 1716

    $\texttt{SPECS}$: Faster Test-Time Scaling through Speculative Drafts by Cemri, Mert, Rajaraman, Nived, Tiwari, Rishabh, Liu, Xiaoxuan, Keutzer, Kurt, Stoica, Ion, Ramchandran, Kannan, Beirami, Ahmad, Sun, Ziteng

    Published 2025
    Table of Contents: “…{SPECS}$, a latency-aware test-time scaling method inspired by speculative decoding. $\texttt{SPECS…”
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  17. 1717

    INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling by Dong, Xin, Dong, Shichao, Wang, Jin, Huang, Jing, Zhou, Li, Sun, Zenghui, Jing, Lihua, Lan, Jingsong, Zhu, Xiaoyong, Zheng, Bo

    Published 2025
    Table of Contents: “… further propose \textbf{INTER}: \textbf{Inter}action Guidance Sampling, a novel training-free algorithm…”
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  18. 1718

    Teaching Transformers to Solve Combinatorial Problems through Efficient Trial & Error by Giannoulis, Panagiotis, Pantis, Yorgos, Tzamos, Christos

    Published 2025
    Table of Contents: “…. Unlike prior work that used custom architectures, our method employs a vanilla decoder-only Transformer…”
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  19. 1719

    AMLA: MUL by ADD in FlashAttention Rescaling by Liao, Qichen, Hu, Chengqiu, Miao, Fangzheng, Li, Bao, Liu, Yiyang, Lyu, Junlong, Jiang, Lirui, Wang, Jun, Zheng, Lingchao, Li, Jun, Fan, Yuwei

    Published 2025
    Table of Contents: “…. This poses challenges for efficient hardware implementation -- especially during the decode phase. This paper…”
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  20. 1720

    The dimension and Bose distance of some BCH codes of length $\frac{q^{m}-1}λ$ by Zheng, Run, Sze, Nung-Sing, Huang, Zejun

    Published 2025
    Table of Contents: “… structure, multi-error correcting capability, and efficient decoding algorithms. Despite their practical…”
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