Miracle-dz/UniFAR-FTUs huggingface dataset:
GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling

Multi-intent SLU can handle multiple intents in an utterance, which has attracted increasing attention. However, the state-of-the-art joint models heavily rely on autoregressive approaches, resulting in two issues: slow inference speed and information leakage. In this paper, we explore a non-autoregressive model for joint multiple intent detection and slot filling, achieving more fast and accurate. Specifically, we propose a Global-Locally Graph Interaction Network (GL-GIN) where a local slot-aware graph interaction layer is proposed to model slot dependency for alleviating uncoordinated slots problem while a global intent-slot graph interaction layer is introduced to model the interaction between multiple intents and all slots in the utterance. Experimental results on two public datasets show that our framework achieves state-of-the-art performance while being 11.5 times faster.
The almost periodic gauge transform -- An abstract scheme with applications to Dirac Operators

One of the main tools used to understand both qualitative and quantitative spectral behaviour of periodic and almost periodic Schrodinger operators is the method of gauge transform. In this paper, we extend this method to an abstract setting, thus allowing for greater flexibility in its applications that include, among others, matrix-valued operators. In particular, we obtain asymptotic expansions for the density of states of certain almost periodic systems of elliptic operators, including systems of Dirac type. We also prove that a range of periodic systems including the two-dimensional Dirac operators satisfy the Bethe--Sommerfeld property, that the spectrum contains a semi-axis -- or indeed two semi-axes in the case of operators that are not semi-bounded.
Evaluating the Efficacy of Summarization Evaluation across Languages

While automatic summarization evaluation methods developed for English are routinely applied to other languages, this is the first attempt to systematically quantify their panlinguistic efficacy. We take a summarization corpus for eight different languages, and manually annotate generated summaries for focus (precision) and coverage (recall). Based on this, we evaluate 19 summarization evaluation metrics, and find that using multilingual BERT within BERTScore performs well across all languages, at a level above that for English.
MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain

Crowdworker-constructed natural language inference (NLI) datasets have been found to contain statistical artifacts associated with the annotation process that allow hypothesis-only classifiers to achieve better-than-random performance (CITATION). We investigate whether MedNLI, a physician-annotated dataset with premises extracted from clinical notes, contains such artifacts (CITATION). We find that entailed hypotheses contain generic versions of specific concepts in the premise, as well as modifiers related to responsiveness, duration, and probability. Neutral hypotheses feature conditions and behaviors that co-occur with, or cause, the condition(s) in the premise. Contradiction hypotheses feature explicit negation of the premise and implicit negation via assertion of good health. Adversarial filtering demonstrates that performance degrades when evaluated on the difficult subset. We provide partition information and recommendations for alternative dataset construction strategies for knowledge-intensive domains.
TVDIM: Enhancing Image Self-Supervised Pretraining via Noisy Text Data

Among ubiquitous multimodal data in the real world, text is the modality generated by human, while image reflects the physical world honestly. In a visual understanding application, machines are expected to understand images like human. Inspired by this, we propose a novel self-supervised learning method, named Text-enhanced Visual Deep InfoMax (TVDIM), to learn better visual representations by fully utilizing the naturally-existing multimodal data. Our core idea of self-supervised learning is to maximize the mutual information between features extracted from multiple views of a shared context to a rational degree. Different from previous methods which only consider multiple views from a single modality, our work produces multiple views from different modalities, and jointly optimizes the mutual information for features pairs of intra-modality and inter-modality. Considering the information gap between inter-modality features pairs from data noise, we adopt a \emph{ranking-based} contrastive learning to optimize the mutual information. During evaluation, we directly use the pre-trained visual representations to complete various image classification tasks. Experimental results show that, TVDIM significantly outperforms previous visual self-supervised methods when processing the same set of images.
Change-Point Analysis of Time Series with Evolutionary Spectra

This paper develops change-point methods for the time-varying spectrum of a time series. We focus on time series with a bounded spectral density that change smoothly under the null hypothesis but exhibits change-points or becomes less smooth under the alternative. We provide a general theory for inference about the degree of smoothness of the spectral density over time. We address two local problems. The first is the detection of discontinuities (or breaks) in the spectrum at unknown dates and frequencies. The second involves abrupt yet continuous changes in the spectrum over a short time period at an unknown frequency without signifying a break. We consider estimation and minimax-optimal testing. We determine the optimal rate for the minimax distinguishable boundary, i.e., the minimum break magnitude such that we are still able to uniformly control type I and type II errors. We propose a novel procedure for the estimation of the change-points based on a wild sequential top-down algorithm and show its consistency under shrinking shifts and possibly growing number of change-points. Our method can be used across many fields and a companion program is made available in popular software packages. AMS 2020 Classification: 62G05, 62G10, 62M15.
The effect of droplet coalescence on drag in turbulent channel flows

Ianto Cannon,1 Daulet Izbassarov,2 Outi Tammisola,3 Luca Brandt,3 and Marco E. Rosti1, a) 1)Complex Fluids and Flows Unit, Okinawa Institute of Science and Technology Graduate University, 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan 2)Department of Mechanical Engineering, Aalto University, FI-00076 Aalto, Finland 3)Linné Flow Centre and SeRC (Swedish e-Science Research Centre), KTH Department of Engineering Mechanics, SE 100 44 Stockholm, Sweden
Cross-Domain First Person Audio-Visual Action Recognition through Relative Norm Alignment

First person action recognition is an increasingly researched topic because of the growing popularity of wearable cameras. This is bringing to light cross-domain issues that are yet to be addressed in this context. Indeed, the information extracted from learned representations suffers from an intrinsic environmental bias. This strongly affects the ability to generalize to unseen scenarios, limiting the application of current methods in real settings where trimmed labeled data are not available during training. In this work, we propose to leverage over the intrinsic complementary nature of audio-visual signals to learn a representation that works well on data seen during training, while being able to generalize across different domains. To this end, we introduce an audio-visual loss that aligns the contributions from the two modalities by acting on the magnitude of their feature norm representations. This new loss, plugged into a minimal multi-modal action recognition architecture, leads to strong results in cross-domain first person action recognition, as demonstrated by extensive experiments on the popular EPIC-Kitchens dataset.
Neutron occupancies and single-particle energies across the stable tin isotopes

S. V. Szwec, ∗ D. K. Sharp, † B. P. Kay, ‡ S. J. Freeman, J. P. Schiffer, P. Adsley, § C. Binnersley, N. de Séréville, T. Faestermann, 5 R. F. Garcia Ruiz, ¶ F. Hammache, R. Hertenberger, 6 A. Meyer, I. Stefan, A. Vernon, ¶ S. Wilkins, ¶ and H. -F. Wirth 6 Department of Physics and Astronomy, University of Manchester, Manchester M13 9PL, United Kingdom Physics Division, Argonne National Laboratory, Lemont, Illinois 60439, USA Université Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay, France Physik Department E12, Technische Universität München, D-85748 Garching, Germany Maier-Leibnitz Laboratorium der Münchner Universitäten (MLL), D-85748 Garching, Germany Fakultät für Physik, Ludwig-Maximillians Universität München, D-85748 Garching, Germany
CCPM: A Chinese Classical Poetry Matching Dataset

Poetry is one of the most important art forms of human languages. Recently many studies have focused on incorporating some linguistic features of poetry, such as style and sentiment, into its understanding or generation system. However, there is no focus on understanding or evaluating the semantics of poetry. Therefore, we propose a novel task to assess a model's semantic understanding of poetry by poem matching. Specifically, this task requires the model to select one line of Chinese classical poetry among four candidates according to the modern Chinese translation of a line of poetry. To construct this dataset, we first obtain a set of parallel data of Chinese classical poetry and modern Chinese translation. Then we retrieve similar lines of poetry with the lines in a poetry corpus as negative choices. We name the dataset Chinese Classical Poetry Matching Dataset (CCPM) and release it at https://github.com/THUNLP-AIPoet/CCPM. We hope this dataset can further enhance the study on incorporating deep semantics into the understanding and generation system of Chinese classical poetry. We also preliminarily run two variants of BERT on this dataset as the baselines for this dataset.
Barbershop

Seamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different parts of the image. Even though recent work on GANs enables synthesis of realistic hair or faces, it remains difficult to combine them into a single, coherent, and plausible image rather than a disjointed set of image patches. We present a novel solution to image blending, particularly for the problem of hairstyle transfer, based on GAN-inversion. We propose a novel latent space for image blending which is better at preserving detail and encoding spatial information, and propose a new GAN-embedding algorithm which is able to slightly modify images to conform to a common segmentation mask. Our novel representation enables the transfer of the visual properties from multiple reference images including specific details such as moles and wrinkles, and because we do image blending in a latent-space we are able to synthesize images that are coherent. Our approach avoids blending artifacts present in other approaches and finds a globally consistent image. Our results demonstrate a significant improvement over the current state of the art in a user study, with users preferring our blending solution over 95 percent of the time. Source code for the new approach is available at https://zpdesu.github. io/Barbershop.
PII: S0925-4773(01)00394-X

The neural crest is an intriguing cell population that gives rise to many derivatives which are all generated far from their ®nal destinations. From its induction to the delamination of the cells, multiple signalling pathways converge to regulate the expression of effector genes, the products of which endow the cells with invasive and migratory properties reminiscent of those displayed by malignant cells in tumours. As such, the neural crest constitutes an excellent model to study cell migration. q 2001 Elsevier Science Ireland Ltd. All rights reserved.
Memory AMP

Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique for certain high-dimensional linear systems with non-Gaussian distributions. AMP only applies to independent identically distributed (IID) transform matrices, but may become unreliable (e.g., perform poorly or even diverge) for other matrix ensembles, especially for ill-conditioned ones. To solve this issue, orthogonal/vector AMP (OAMP/VAMP) was proposed for general right-unitarily-invariant matrices. However, the Bayes-optimal OAMP/VAMP (BO-OAMP/VAMP) requires a high-complexity linear minimum mean square error (MMSE) estimator. This prevents OAMP/VAMP from being used in large-scale systems. To address the drawbacks of AMP and BO-OAMP/VAMP, this paper offers a memory AMP (MAMP) framework based on the orthogonality principle, which ensures that estimation errors in MAMP are asymptotically IID Gaussian. To realize the required orthogonality for MAMP, we provide an orthogonalization procedure for the local memory estimators. In addition, we propose a Bayes-optimal MAMP (BO-MAMP), in which a long-memory matched filter is used for interference suppression. The complexity of BO-MAMP is comparable to AMP. To asymptotically characterize the performance of BO-MAMP, a state evolution is derived. The relaxation parameters and damping vector in BO-MAMP are optimized based on state evolution. Most crucially, the state evolution of the optimized BO-MAMP converges to the same fixed point as that of the high-complexity BO-OAMP/VAMP for all right-unitarily-invariant matrices, and achieves the Bayes optimal MSE predicted by the replica method if its state evolution has a unique fixed point. Finally, simulations are provided to verify the theoretical results’ validity and accuracy.
PII: S0925-4773(01)00547-0

The HMG-domain transcription factor Sox10 is essential for the development of various neural crest derived lineages including glia and neurons of the peripheral nervous system (PNS). Within the PNS the most striking defect is the complete absence of glial differentiation whereas neurogenesis seemed initially normal. A degeneration of motoneurons and sensory neurons occurred later in development. The mechanism that leads to the dramatic effects on the neural crest derived cell lineages in the dorsal root ganglia (DRG), however, has not been examined up to now. Here, we provide a detailed analysis of proliferation and apoptosis in the DRG during the time of their generation and lineage segregation (between E 9.5 and E 11.5). We show that both increased apoptosis as well as decreased proliferation of neural crest cells contribute to the observed hypomorphism. q 2001 Elsevier Science Ireland Ltd. All rights reserved.
PII: S0925-4773(99)00338-X

Drosophila minidiscs mutant larvae have smaller imaginal discs than wild-type larvae. However, transplantation experiments have revealed that minidiscs mutant imaginal discs can grow if cultured in non-mutant hosts. These data suggest that minidiscs is required in one or more non-imaginal tissues for synthesis and/or secretion of a diffusible factor that stimulates imaginal cell proliferation. The 2.3 kb minidiscs transcript accumulates in the larval fat body and encodes a protein containing 12 putative membrane spanning domains that is similar in sequence to amino acid transporter subunits from other eukaryotes, including humans. We propose that in response to amino acid uptake by the transporter encoded by minidiscs, the fat body secretes a diffusible factor required for imaginal disc proliferation. q 2000 Elsevier Science Ireland Ltd. All rights reserved.
PII: S0042-6989(01)00207-3

Presenting a distractor prolongs not only saccadic reaction times in paced tasks but also fixation durations in unpaced tasks. To investigate whether the effect of a distractor is a pure optomotor reflex, we used both visual and auditory distractors in an unpaced picture-viewing paradigm. Results show a distractor effect for both modalities. Analysis of data from previous studies showed similar effects, even in amodal shifts of attention. These findings challenge the hypothesis that the effect is modality-specific and suggest that the distractor effect may be another expression of the orienting reflex. © 2001 Published by Elsevier Science Ltd.
PII: S0925-4773(01)00591-3

Development and differentiation of the vertebrate caudal midbrain and anterior hindbrain are dependent on the isthmic organizer signals at the midbrain/hindbrain boundary (MHB). The future MHB forms at the boundary between the Otx2 and Gbx2 expression domains. Recent studies in mice and chick suggested that the apposition of Otx2and Gbx2-expressing cells is instrumental for the positioning and early induction of the MHB genetic cascade. We show that Otx2 and Gbx2 perform different roles in this process. We find that ectopically expressed Otx2 on its own can induce a substantial part of the MHB genetic network, namely En2, Wnt1, Pax-2, Fgf8 and Gbx2, in a concentration-dependent manner. This induction does not require protein synthesis and ends during neurulation. In contrast, Gbx2 is a negative regulator of Otx2 and the MHB genes. Based on the temporal patterns of expression of the genes involved, we propose that Otx2 might be the early inducer of the isthmic organizer genetic network while Gbx2 restricts Otx2 expression along the anterior-posterior axis and establishes an Otx2 gradient. q 2002 Elsevier Science Ltd. All rights reserved.
PII: S0042-6989(01)00060-8

We wished to identify the different types of retinal neurons on the basis of their content of neuroactive substances in both larval tiger salamander and mudpuppy retinas, favored species for electrophysiological investigation. Sections and wholemounts of retinas were labeled by immunocytochemical methods to demonstrate three calcium binding protein species and the common neurotransmitters, glycine, GABA and acetylcholine. Double immunostained sections and single labeled wholemount retinas were examined by confocal microscopy. Immunostaining patterns appeared to be the same in salamander and mudpuppy. Double and single cones, horizontal cells, some amacrine cells and ganglion cells were strongly calbindin-immunoreactive (IR). Calbindin-IR horizontal cells colocalized GABA. Many bipolar cells, horizontal cells, some amacrine cells and ganglion cells were strongly calretinin-IR. One type of horizontal cell and an infrequently occurring amacrine cell were parvalbumin-IR. Acetylcholine as visualized by ChAT-immunoreactivity was seen in a mirror-symmetric pair of amacrine cells that colocalized GABA and glycine. Glycine and GABA colocalized with calretinin, calbindin and occasionally with parvalbumin in amacrine cells. © 2001 Elsevier Science Ltd. All rights reserved.
Dissolved air flotation separation for pretreatment of membrane bioreactor in domestic wastewater treatment

Due to requiring higher water quality standards over time, new technologies are being employed for wastewater treatment. Dissolved air flotation (DAF) and membrane bioreactor (MBR) technologies are widely employed as new technologies in wastewater treatment. DAF is used due to its excellent separation capability of suspended solids as well as oily material. MBR is used because it may provide a high level of mixed liquor suspended solids in a biological system and excellent separation capability too. In the investigation, separation by DAF, without addition of coagulant, could remove chemical oxygen demand by potassium dicromate (COD cr ) up to over 70%, biochemical oxygen demand (BOD 5 ) 73%, suspended solids (SS) 83%, total nitrogen (T-N) 55%, and total phosphorus (T-P) 65% in influent of municipal wastewater. Average overall removal rates of water quality parameters by the DAF-MBR system were very high such as COD cr 95.9%, BOD 5 99.7%, chemical oxygen demand by potassium permanganate) 93.6%, T-N 69.8%, NH 4 -N 98.5%, T-P 78.2%, and SS 99.5%, which satisfy effluent water quality standards. Membrane separation in the MBR system produced a very low SS concentration of 1.27 mg/l in the final effluent. It was proven that DAF separation is an excellent technology for pretreatment of wastewater treatment, especially for an MBR system.
PII: S0925-4773(02)00119-3

We show that high levels of Hedgehog signaling activity are essential for medial-region patterning in Drosophila legs. In mid-to-late third instar leg discs, high levels of Hedgehog signals repress the transcription of pxb, a newly identified gene encoding a transmembrane protein expressed specifically in the anterior compartment. Misexpression experiments indicate that Pxb may serve as a Hedgehog signaling attenuator capable of acting prior to Hedgehog–Patched interactions, suggesting that Hedgehog signaling in leg discs includes a pxbrepression-mediated positive feedback loop. RNA interference and clonal analysis show that neither Wingless nor Decapentaplegic signaling is required for pxb repression but high levels of Wingless signaling activity are essential for patterning in the leg ventral medial region. q 2002 Elsevier Science Ireland Ltd. All rights reserved.
PII: S0925-4773(00)00573-6

The imprinted Igf2 gene is active only on the paternal allele in most tissues. Its imprinting involves a cis-acting imprinting-control region (ICR) located upstream of the neighboring and maternally expressed H19 gene. It is thought that differential methylation of the parental alleles at the ICR is crucial for parental imprinting of both genes. Differentially methylated regions (DMRs) have also been identi®ed within the Igf2 gene and their differential methylation is thought to be established during early development. To gain further insight into the function of these DMRs, we performed a quantitative analysis of their allelic methylation levels in different tissues during fetal development and the postnatal period in the mouse. Surprisingly, we found that the methylation levels of Igf2 DMRs vary extensively during fetal development, mostly on the expressed paternal allele. In particular, in skeletal muscle, differential allelic methylation in both DMR 1 and DMR 2 occurs only after birth, whereas correct paternal monoallelic expression is always observed, including in the embryonic stages. This suggests that differential methylation in the DMR 1 and DMR 2 of the Igf2 gene is dispensable for its imprinting in skeletal muscle. Furthermore, progressive methylation of the Igf2 paternal allele appears to be correlated with concomitant postnatal down-regulation and silencing of the gene. We discuss possible relations between Igf2 allelic methylation and expression during fetal development. q 2001 Elsevier Science Ireland Ltd. All rights reserved.
PII: S0042-6989(97)00433-1

The aim of the study was to obtain normal values for the colour-arrangement test, Roth 28-hue desaturated. In 146 healthy non-smokers colour vision was tested monocularly. The subjects were divided into four age groups: 0–19, 20–39, 40–59, and 60–79 years. The overall error score for all groups was 54924 (median 9 mean absolute deviation). The values for the 20–39 year group were significantly lower than those for the other groups (Kruskal-Wallis: PB0.0001 with subsequent multiple Mann-Whitney test). An increasing predominance of errors along the blue-yellow-axis was observed with increasing age. The error scores of normal subjects tested by the Roth 28-hue desaturated were comparable with those on the well-known Farnsworth-Munsell 100-hue (FM-100). Because the Roth 28-hue desaturated is shorter and simpler to administer, it is an alternative to the FM-100 in situations that need to assess colour discrimination and error axis quantitatively and quickly. © 1998 Elsevier Science Ltd. All rights reserved.