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Transactions of the Association for Computational Linguistics, 2022 Decoding for many NLP tasks requires an effective heuristic algorithm for approximating exact search because the problem of searching the full output space is often intractable, or impractical in many settings. The default algorithm for this job is beam search—a pruned version of breadth-first search.
Clara Meister +2 more
doaj +7 more sources
A Beam Search Framework for Quantum Circuit Mapping [PDF]
EntropyIn the era of noisy intermediate-scale quantum (NISQ) computing, the limited connectivity between qubits is one of the common physical limitations faced by current quantum computing devices. Quantum circuit mapping methods transform quantum circuits into
Cheng Qiu, Pengcheng Zhu, Lihua Wei
doaj +4 more sources
Finding Syntax in Human Encephalography with Beam Search [PDF]
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018 ACL2018
John K. Hale +3 more
semanticscholar +6 more sources
Determinantal Beam Search [PDF]
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021 Beam search is a go-to strategy for decoding neural sequence models. The algorithm can naturally be viewed as a subset optimization problem, albeit one where the corresponding set function does not reflect interactions between candidates. Empirically, this leads to sets often exhibiting high overlap, e.g., strings may differ by only a single word.
Meister, Clara Isabel; id_orcid0000-0002-3775-4426 +2 more
openaire +6 more sources
Meshed Context-Aware Beam Search for Image Captioning [PDF]
EntropyBeam search is a commonly used algorithm in image captioning to improve the accuracy and robustness of generated captions by finding the optimal word sequence. However, it mainly focuses on the highest-scoring sequence at each step, often overlooking the
Fengzhi Zhao +3 more
doaj +2 more sources
Dynamic sub-route-based self-adaptive beam search Q-learning algorithm for traveling salesman problem. [PDF]
PLoS ONE, 2023 In this paper, a dynamic sub-route-based self-adaptive beam search Q-learning (DSRABSQL) algorithm is proposed that provides a reinforcement learning (RL) framework combined with local search to solve the traveling salesman problem (TSP). DSRABSQL builds
Jin Zhang, Qing Liu, XiaoHang Han
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X17 search project with EAR2 neutron beam [PDF]
EPJ Web of Conferences, 2023 We present the state of the art of the n_TOF Collaboration Working Group activity dedicated to study how to solve the puzzle about the existence of the so called new particle X17, spotted for the first time few years ago by a team at ATOMKI in Hungary ...
Gervino Gianpiero +12 more
doaj +3 more sources
Pentaquark Search with Energetic Hadron Beams
, 1994 12 pages text (latex) uses charm2000.sty file (appended), which requires extracting and setting up charm2000.sty in your directory, in addition to the tex file, TAUP-2179-94, submitted to CHARM2000 workshop proceedings, revised July 19 to correct reference, revised Aug. 5 for additional proofreading corrections, revised Aug.
M. A. Moinester +3 more
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Beam Purity for Light Dark Matter Search in Beam Dump Experiments [PDF]
Advances in High Energy Physics, 2015 This paper reviews the search for light dark matter in beam dump experiments with a special emphasis on the necessity of beam purity for precise background rejection at the sensitivities aimed at these experiments.
D. Banerjee, P. Crivelli, A. Rubbia
doaj +4 more sources
A Continuous Relaxation of Beam Search for End-to-End Training of Neural Sequence Models
, 2018 Beam search is a desirable choice of test-time decoding algorithm for neural sequence models because it potentially avoids search errors made by simpler greedy methods.
Kartik Goyal +3 more
openalex +4 more sources