Measuring alignment bias in neural Seq2Seq semantic parsers

Prior to deep learning the semantic parsing community has been interested in understanding and modeling the range of possible word alignments between natural language sentences and their corresponding meaning representations. Sequence-to-sequence models changed the research landscape suggesting that we no longer need to worry about alignments since they can be learned automatically by means of an attention mechanism. More recently, researchers have started to question such premise. In this work we investigate whether seq2seq models can handle both simple and complex alignments. To answer this question we augment the popular GEO semantic parsing dataset with alignment annotations and create GEO-ALIGNED. We then study the performance of standard seq2seq models on the examples that can be aligned monotonically versus examples that require more complex alignments. Our empirical study shows that performance is significantly better over monotonic alignments.This work is supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No.853459).Peer ReviewedPostprint (published version

Authors' reply to: Letter to editor regarding "The endoscopic diving technique in endonasal transsphenoidal surgery: how I do it"

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Translate First Reorder Later: Leveraging Monotonicity in Semantic Parsing

Prior work in semantic parsing has shown that conventional seq2seq models fail at compositional generalization tasks. This limitation led to a resurgence of methods that model alignments between sentences and their corresponding meaning representations, either implicitly through latent variables or explicitly by taking advantage of alignment annotations. We take the second direction and propose TPol, a two-step approach that first translates input sentences monotonically and then reorders them to obtain the correct output. This is achieved with a modular framework comprising a Translator and a Reorderer component. We test our approach on two popular semantic parsing datasets. Our experiments show that by means of the monotonic translations, TPol can learn reliable lexico-logical patterns from aligned data, significantly improving compositional generalization both over conventional seq2seq models, as well as over a recently proposed approach that exploits gold alignments.Comment: 8 pages, 4 figures, 4 table

Allogeneic hematopoietic stem cell transplantation for pediatric acute myeloid leukemia in first complete remission: a meta-analysis

Identification of pediatric patients with acute myeloid leukemia (AML) candidates to receive allogeneic hematopoietic stem cell transplantation (allo-HSCT) in first complete remission (CR1) is still a matter of debate. Currently, transplantation is reserved to patients considered at high risk of relapse based on cytogenetics, molecular biology, and minimal residual disease (MRD) assessment. However, no randomized clinical trial exists in the literature comparing transplantation with other types of consolidation therapy. Here, we provide an up-to-date meta-analysis of studies comparing allo-HSCT in CR1 with chemotherapy alone as a post-remission treatment in high-risk pediatric AML. The literature search strategy identified 10 cohorts from 9 studies performing as-treated analysis. The quantitative synthesis showed improved overall survival (OS) (relative risk, 1.15; 95% confidence interval [CI], 1.06-1.24; P = 0.0006) and disease-free survival (relative risk, 1.31; 95% CI, 1.17-1.47; P = 0.0001) in the allo-HSCT group, with increased relapse rate in the chemotherapy group (relative risk, 1.26; 95% CI, 1.07-1.49; P = 0.006). Sensitivity analysis including prospective studies alone and excluding studies that reported the comparison only on intermediate-risk patients confirmed the benefit of allo-HSCT on OS. Further research should focus on individualizing allo-HSCT indications based on molecular stratification and MRD monitoring

Joint state and parameter estimation based on constrained zonotopes

This note presents a new method for set-based joint state and parameter estimation of discrete-time systems using constrained zonotopes. This is done by extending previous set-based state estimation methods to include parameter identification in a unified framework. Unlike in interval-based methods, the existing dependencies between states and model parameters are maintained from one time step to the next, thus providing a more accurate estimation scheme. In addition, the enclosure of states and parameters is refined using measurements through generalized intersections, which are properly captured by constrained zonotopes. The advantages of the new approach are highlighted in two numerical examples

Combined NMDA Inhibitor Use in a Patient With Multisubstance-induced Psychotic Disorder

This document is an Accepted Manuscript reprinted from Journal of Addiction Medicine, Vol. 12 (3): 247-251, May 2018, with permission of Kluwer Law International. Under embargo until 1 May 2019. The Version of Record is available online at DOI: https://doi.org/10.1097/ADM.0000000000000390: Novel psychoactive substance use is a major social concern. Their use may elicit or uncover unpredictably as yet undescribed clinical pictures. We aimed to illustrate a multisubstance use case indistinguishable from paranoid schizophrenia, so to alert clinicians on possibly misdiagnosing substance-induced psychotic disorders. CASE REPORT: We describe a case of a 32-year-old man who started at 18 years with cannabinoids and ketamine, and is currently using N-methyl-D-aspartate (NMDA) antagonists. At age 23, he developed social withdrawal after being assaulted by a stranger, but did not consult psychiatrists until age 26; during this period, he was using internet-purchased methoxetamine and ketamine, and was persecutory, irritable, suspicious, and insomniac and discontinued all received medical prescriptions. He added dextromethorphan to his list of used substances. At age 31, while using phencyclidine, and, for the first time, methoxphenidine, he developed a religious delusion, involving God calling him to reach Him, and the near-death experiences ensured by NMDA antagonists backed his purpose. He received Diagnostic and Statistical Manual of Mental Disorders, 5th Edition diagnosis of multisubstance-induced psychotic disorder and was hospitalized 8 times, 6 of which after visiting the emergency room due to the development of extreme anguish, verbal and physical aggression, and paranoia. He reportedly used methoxphenidine, methoxyphencyclidine, ethylnorketamine, norketamine, and deschlorketamine, to achieve near-death experiences, and eventually to reach God in heavens. CONCLUSIONS: This case points to the need for better control of drugs sold on the internet. It also illustrates that people using NMDA antagonists may present clinical pictures indistinguishable from those of major psychoses and are likely to be misdiagnosed.Peer reviewe

Nonlinear asymmetric imaging with AlGaAs metasurface

Nowadays, dielectric metasurfaces are a promising platform in many different research fields such as sensing, lasing, all-optical modulation and nonlinear optics. Among all the different kinds of such thin structures, asymmetric geometries are recently attracting increasing interest. In particular, nonlinear light-matter interaction in metasurfaces constitutes a valid approach for achieving miniaturized control over light. Here, we demonstrate nonlinear asymmetric generation of light in a dielectric metasurface via second harmonic generation. By inverting the illumination direction of the pump, the nonlinear emitted power is modulated by more than one order of magnitude. Moreover, we demonstrate how a properly designed metasurface can generate two completely different images at the second harmonic when the direction of illumination is reversed. Our results may pave the way to important opportunities for the realization of compact nanophotonic devices for imaging applications by densely integrating numerous nonlinear resonators