Results 41 to 50 of about 4,199,032 (361)
Anomaly Detection in Smart Homes Using Deep Learning [PDF]
Iranica Journal of Energy and Environment, 2019 Smart homes enable many people, especially the elderly and patients, to live alone and maintain their independence and comfort. The realization of this goal depends on monitoring all activities in the house to report any observed anomaly immediately to ...
M. Moallem, H. Hassanpour, A. A. Pouyan
doaj +1 more source
TABS: Efficient Textual Adversarial Attack for Pre-trained NL Code Model Using Semantic Beam Search
Conference on Empirical Methods in Natural Language Processing, 2022 As pre-trained models have shown successful performance in program language processing as well as natural language processing, adversarial attacks on these models also attract attention.However, previous works on black-box adversarial attacks generated ...
YunSeok Choi, Hyojun Kim, Jee-Hyong Lee
semanticscholar +1 more source
Sterile neutrino searches at tagged kaon beams [PDF]
Physical Review D, 2021 Tagged kaon beams are attractive neutrino sources, which would provide flavor pure $ _e$-beams with exactly measured normalization. We point out that this also leads to an anti-tagged flavor pure $ _ $-beam, with equally well known normalization. Exposing a 1 kt liquid argon detector at a baseline of 1 km to this combination of unique beams allows ...
Delgadillo, Luis A., Huber, Patrick
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A Hardware-Oriented and Memory-Efficient Method for CTC Decoding
IEEE Access, 2019 The Connectionist Temporal Classification (CTC) has achieved great success in sequence to sequence analysis tasks such as automatic speech recognition (ASR) and scene text recognition (STR).
Siyuan Lu +3 more
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A Combined Extractive With Abstractive Model for Summarization
IEEE Access, 2021 Aiming at the difficulties in document-level summarization, this paper presents a two-stage, extractive and then abstractive summarization model. In the first stage, we extract the important sentences by combining sentences similarity matrix (only used ...
Wenfeng Liu +3 more
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Entropy-Based Dynamic Rescoring with Language Model in E2E ASR Systems
Applied Sciences, 2022 Language models (LM) have played crucial roles in automatic speech recognition (ASR), whether as an essential part of a conventional ASR system composed of an acoustic model and LM, or as an integrated model to enhance the performance of novel end-to-end
Zhuo Gong +2 more
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Speculative Beam Search for Simultaneous Translation [PDF]
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019 accepted by EMNLP ...
Renjie Zheng +3 more
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Sequence-to-Sequence Learning as Beam-Search Optimization [PDF]
Conference on Empirical Methods in Natural Language Processing, 2016 Sequence-to-Sequence (seq2seq) modeling has rapidly become an important general-purpose NLP tool that has proven effective for many text-generation and sequence-labeling tasks.
Sam Wiseman, Alexander M. Rush
semanticscholar +1 more source
Diverse Decoding for Abstractive Document Summarization
Applied Sciences, 2019 Recently, neural sequence-to-sequence models have made impressive progress in abstractive document summarization. Unfortunately, as neural abstractive summarization research is in a primitive stage, the performance of these models is still far from ideal.
Xu-Wang Han +3 more
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Searching for a U-boson with a positron beam [PDF]
AIP Conference Proceedings, 2009 A high sensitivity search for a light \Ub{} by means of a positron beam incident on a hydrogen target is proposed. We described a concept of the experiment and two possible realizations. The projected result of this experiment corresponds to an upper limit on the square of coupling constant $ |f_{_{eU}}|^2 = 3 \times 10^{-9}$ with a signal to noise ...
B. Wojtsekhowski +5 more
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