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Found 6 papers, 4 papers with code
ValCAT: Variable-Length Contextualized Adversarial Transformations Using Encoder-Decoder Language Model
Adversarial texts help explore vulnerabilities in language models, improve model robustness, and explain their working mechanisms.
Cybersecurity Entity Alignment via Masked Graph Attention Networks
Cybersecurity vulnerability information is often recorded by multiple channels, including government vulnerability repositories, individual-maintained vulnerability-gathering platforms, or vulnerability-disclosure email lists and forums.
Learning Security Classifiers with Verified Global Robustness Properties
Since data distribution shift is very common in security applications, e. g., often observed for malware detection, local robustness cannot guarantee that the property holds for unseen inputs at the time of deploying the classifier.
Agricultural risks from changing snowmelt.
Snowpack stores cold-season precipitation to meet warm-season water demand.
Otem&Utem: Over- and Under-Translation Evaluation Metric for NMT
Although neural machine translation(NMT) yields promising translation performance, it unfortunately suffers from over- and under-translation is- sues [Tu et al., 2016], of which studies have become research hotspots in NMT.
Asynchronous Bidirectional Decoding for Neural Machine Translation
The dominant neural machine translation (NMT) models apply unified attentional encoder-decoder neural networks for translation.
