94 research outputs found
Assigning personality/identity to a chatting machine for coherent conversation generation
Endowing a chatbot with personality or an identity is quite challenging but
critical to deliver more realistic and natural conversations. In this paper, we
address the issue of generating responses that are coherent to a pre-specified
agent profile. We design a model consisting of three modules: a profile
detector to decide whether a post should be responded using the profile and
which key should be addressed, a bidirectional decoder to generate responses
forward and backward starting from a selected profile value, and a position
detector that predicts a word position from which decoding should start given a
selected profile value. We show that general conversation data from social
media can be used to generate profile-coherent responses. Manual and automatic
evaluation shows that our model can deliver more coherent, natural, and
diversified responses.Comment: an error on author informatio
Exploiting modality-invariant feature for robust multimodal emotion recognition with missing modalities
Multimodal emotion recognition leverages complementary information across
modalities to gain performance. However, we cannot guarantee that the data of
all modalities are always present in practice. In the studies to predict the
missing data across modalities, the inherent difference between heterogeneous
modalities, namely the modality gap, presents a challenge. To address this, we
propose to use invariant features for a missing modality imagination network
(IF-MMIN) which includes two novel mechanisms: 1) an invariant feature learning
strategy that is based on the central moment discrepancy (CMD) distance under
the full-modality scenario; 2) an invariant feature based imagination module
(IF-IM) to alleviate the modality gap during the missing modalities prediction,
thus improving the robustness of multimodal joint representation. Comprehensive
experiments on the benchmark dataset IEMOCAP demonstrate that the proposed
model outperforms all baselines and invariantly improves the overall emotion
recognition performance under uncertain missing-modality conditions. We release
the code at: https://github.com/ZhuoYulang/IF-MMIN.Comment: 5 pages, 3 figures, 1 table. Submitted to ICASSP 2023. We release the
code at: https://github.com/ZhuoYulang/IF-MMI
Multimodal Short Video Rumor Detection System Based on Contrastive Learning
With short video platforms becoming one of the important channels for news
sharing, major short video platforms in China have gradually become new
breeding grounds for fake news. However, it is not easy to distinguish short
video rumors due to the great amount of information and features contained in
short videos, as well as the serious homogenization and similarity of features
among videos. In order to mitigate the spread of short video rumors, our group
decides to detect short video rumors by constructing multimodal feature fusion
and introducing external knowledge after considering the advantages and
disadvantages of each algorithm. The ideas of detection are as follows: (1)
dataset creation: to build a short video dataset with multiple features; (2)
multimodal rumor detection model: firstly, we use TSN (Temporal Segment
Networks) video coding model to extract video features; then, we use OCR
(Optical Character Recognition) and ASR (Automatic Character Recognition) to
extract video features. Recognition) and ASR (Automatic Speech Recognition)
fusion to extract text, and then use the BERT model to fuse text features with
video features (3) Finally, use contrast learning to achieve distinction: first
crawl external knowledge, then use the vector database to achieve the
introduction of external knowledge and the final structure of the
classification output. Our research process is always oriented to practical
needs, and the related knowledge results will play an important role in many
practical scenarios such as short video rumor identification and social opinion
control
Role of MicroRNA-26b in Glioma Development and Its Mediated Regulation on EphA2
BACKGROUND: MicroRNAs (miRNAs) are short, non-coding RNAs that regulate the expression of multiple target genes. Deregulation of miRNAs is common in human tumorigenesis. Low level expression of miR-26b has been found in glioma cells. However, its underlying mechanism of action has not been determined. METHODOLOGY/PRINCIPAL FINDINGS: Real-time PCR was employed to measure the expression level of miR-26b in glioma patients and cells. The level of miR-26b was inversely correlated with the grade of glioma. Ectopic expression of miR-26b inhibited the proliferation, migration and invasion of human glioma cells. A binding site for miR-26b was identified in the 3'UTR of EphA2. Over-expression of miR-26b in glioma cells repressed the endogenous level of EphA2 protein. Vasculogenic mimicry (VM) experiments were performed to further confirm the effects of miR-26b on the regulation of EphA2, and the results showed that miR-26b inhibited the VM processes which regulated by EphA2. SIGNIFICANCE: This study demonstrated that miR-26b may act as a tumor suppressor in glioma and it directly regulates EphA2 expression. EphA2 is a direct target of miR-26b, and the down-regulation of EphA2 mediated by miR-26b is dependent on the binding of miR-26b to a specific response element of microRNA in the 3'UTR region of EphA2 mRNA
Spectral signatures of the surface anomalous Hall effect in magnetic axion insulators
The topological surface states of magnetic topological systems, such as Weyl
semimetals and axion insulators, are associated with unconventional transport
properties such as nonzero or half-quantized surface anomalous Hall effect.
Here we study the surface anomalous Hall effect and its spectral signatures in
different magnetic topological phases using both model Hamiltonian and
first-principles calculations. We demonstrate that by tailoring the
magnetization and interlayer electron hopping, a rich three-dimensional
topological phase diagram can be established, including three types of
topologically distinct insulating phases bridged by Weyl semimetals, and can be
directly mapped to realistic materials such as MnBi2Te4/(Bi2Te3)n systems.
Among them, we find that the surface anomalous Hall conductivity in the
axion-insulator phase is a well-localized quantity either saturated at or
oscillating around e2/2h, depending on the magnetic homogeneity. We also
discuss the resultant chiral hinge modes embedded inside the side surface bands
as the potential experimental signatures for transport measurements. Our study
is a significant step forward towards the direct realization of long-sought
axion insulators in realistic material systems.Comment: 22 pages, 4 figure
An unprecedented synergy of high-temperature tensile strength and ductility in a NiCoCrAlTi high-entropy alloy
The present work reported a novel L12-strengthening NiCoCrAlTi high entropy
alloy (HEA) with an outstanding synergy of tensile strength and ductility at
both ambient and high temperatures. Transmission electron microscopy (TEM)
characterization revealed a high density of rod-like and spheroidal L12
precipitates distributing in the micro/nanograins and non-recrystallized
regions in the annealed specimens. The tremendously high yield stress, ultimate
tensile stress (UTS), and ductility of the HEA at 600 C were ~1060 MPa, 1271
MPa, and 25%, respectively, which were significantly superior to most reported
HEAs and Co- and Ni-based superalloys to date. Systematic TEM analysis unveiled
that the cooperation among L12 precipitation, extensive stacking faults (SFs),
deformation twins (DTs), immobile Lomer-Cottrell (L-C) locks formed from
interactions between SFs and SFs/DTs, hierarchical SFs/DTs networks, as well as
hetero-deformation-induced strengthening dominated the plastic deformation at
600 C. Such a unique deformation mechanism enabled extremely high tensile
strength and sustained ductility of the HEA at a high temperature
Diagenesis of the first member of Canglangpu Formation of the Cambrian Terreneuvian in northern part of the central Sichuan Basin and its influence on porosity
In this paper, taking the first Member of the Canglangpu Formation of the Cambrian Terreneuvian in the northern central Sichuan Basin as an example, the diagenesis and its influence on porosity are systemically studied based on the observations and identifications of cores, casts and cathodoluminescence thin sections. The results show that the rock types of the first member of Canglangpu Formation are various, including mixed rocks, carbonate rocks and clastic rocks. The specific lithology is dominated by sand-bearing oolitic dolomite, sandy oolitic dolomite, sparry oolotic dolomite and fine-grained detrital sandstone. At the same time, the Cang 1 Member has experienced five types of diagenetic environments, including seawater, meteoric water, evaporative seawater, shallow burial, and medium-deep burial diagenetic environments. Moreover, the main diagenetic processes under different diagenetic environments include cementation, dissolution, compaction, chemical compaction, dolomitization and structural fractures. According to the analysis, fabric-selective dissolution in meteoric water diagenetic environment, dolomitization in evaporative seawater environment, and non-fabric-selective dissolution, dolomitization and structural fractures in buried diagenetic environment are beneficial to the development of pores. However, cementation, compaction and chemical compaction in medium and deep burial environments, are unfavorable for the development of pores
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