Effects of depolarizing quantum channels on BB84 and SARG04 quantum cryptography protocols

We report experimental studies on the effect of the depolarizing quantum channel on weak-pulse BB84 and SARG04 quantum cryptography. The experimental results show that, in real world conditions in which channel depolarization cannot be ignored, BB84 should perform better than SARG04.Comment: 4 pages, 4 figure

Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue

Video-grounded Dialogue (VGD) aims to decode an answer sentence to a question regarding a given video and dialogue context. Despite the recent success of multi-modal reasoning to generate answer sentences, existing dialogue systems still suffer from a text hallucination problem, which denotes indiscriminate text-copying from input texts without an understanding of the question. This is due to learning spurious correlations from the fact that answer sentences in the dataset usually include the words of input texts, thus the VGD system excessively relies on copying words from input texts by hoping those words to overlap with ground-truth texts. Hence, we design Text Hallucination Mitigating (THAM) framework, which incorporates Text Hallucination Regularization (THR) loss derived from the proposed information-theoretic text hallucination measurement approach. Applying THAM with current dialogue systems validates the effectiveness on VGD benchmarks (i.e., AVSD@DSTC7 and AVSD@DSTC8) and shows enhanced interpretability.Comment: 12 pages, Accepted in EMNLP 202

Round Robin Analyses on Stress Intensity Factors of Inner Surface Cracks in Welded Stainless Steel Pipes

AbstractAustenitic stainless steels (ASSs) are widely used for nuclear pipes as they exhibit a good combination of mechanical properties and corrosion resistance. However, high tensile residual stresses may occur in ASS welds because postweld heat treatment is not generally conducted in order to avoid sensitization, which causes a stress corrosion crack. In this study, round robin analyses on stress intensity factors (SIFs) were carried out to examine the appropriateness of structural integrity assessment methods for ASS pipe welds with two types of circumferential cracks. Typical stress profiles were generated from finite element analyses by considering residual stresses and normal operating conditions. Then, SIFs of cracked ASS pipes were determined by analytical equations represented in fitness-for-service assessment codes as well as reference finite element analyses. The discrepancies of estimated SIFs among round robin participants were confirmed due to different assessment procedures and relevant considerations, as well as the mistakes of participants. The effects of uncertainty factors on SIFs were deducted from sensitivity analyses and, based on the similarity and conservatism compared with detailed finite element analysis results, the R6 code, taking into account the applied internal pressure and combination of stress components, was recommended as the optimum procedure for SIF estimation

Structured Co-reference Graph Attention for Video-grounded Dialogue

A video-grounded dialogue system referred to as the Structured Co-reference Graph Attention (SCGA) is presented for decoding the answer sequence to a question regarding a given video while keeping track of the dialogue context. Although recent efforts have made great strides in improving the quality of the response, performance is still far from satisfactory. The two main challenging issues are as follows: (1) how to deduce co-reference among multiple modalities and (2) how to reason on the rich underlying semantic structure of video with complex spatial and temporal dynamics. To this end, SCGA is based on (1) Structured Co-reference Resolver that performs dereferencing via building a structured graph over multiple modalities, (2) Spatio-temporal Video Reasoner that captures local-to-global dynamics of video via gradually neighboring graph attention. SCGA makes use of pointer network to dynamically replicate parts of the question for decoding the answer sequence. The validity of the proposed SCGA is demonstrated on AVSD@DSTC7 and AVSD@DSTC8 datasets, a challenging video-grounded dialogue benchmarks, and TVQA dataset, a large-scale videoQA benchmark. Our empirical results show that SCGA outperforms other state-of-the-art dialogue systems on both benchmarks, while extensive ablation study and qualitative analysis reveal performance gain and improved interpretability.Comment: Accepted to AAAI202