April 2020 arXiv papers — page 2

I. Tutusaus, M. Martinelli, V. F. Cardone, S. Camera

The data from the Euclid mission will enable the measurement of the photometric redshifts, angular positions, and weak lensing shapes for over a billion galaxies. This large dataset will allow for cosmological analyses using the angular clustering of galaxies and cosmic shear. The cross-correlation (XC) between these probes can tighten constraints and it is

Shuyang Dai, Zhe Gan, Yu Cheng, Chenyang Tao

Natural language often exhibits inherent hierarchical structure ingrained with complex syntax and semantics. However, most state-of-the-art deep generative models learn embeddings only in Euclidean vector space, without accounting for this structural property of language. In this paper, we investigate text generation in a hyperbolic latent space to learn con

M. V. Santucho, H. E. Luparello, M. Lares, D. G. Lambas

Studies of large-scale structures in the Universe, such as superstructures or cosmic voids, have been widely used to characterize the properties of the cosmic web through statistical analyses. On the other hand, the 2-point correlation function of large-scale tracers such as galaxies or halos provides a reliable statistical measure. However, this function ap

Francis O. Afzal, Yusheng Bian, Bo Peng, Shuren Hu

The data communications industry has begun transitioning from electrical to optical interconnects in datacenters in order to overcome performance bottlenecks and meet consumer needs. To mitigate the costs associated with this change and achieve performance for 5G and beyond, it is crucial to explore advanced photonic devices that can enable high-bandwidth in

Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, Sebastian Ruder

The main goal behind state-of-the-art pre-trained multilingual models such as multilingual BERT and XLM-R is enabling and bootstrapping NLP applications in low-resource languages through zero-shot or few-shot cross-lingual transfer. However, due to limited model capacity, their transfer performance is the weakest exactly on such low-resource languages and la

Andreas Lenz, Lorenz Welter, Sven Puchinger

In this paper, we study achievable rates of concatenated coding schemes over a deoxyribonucleic acid (DNA) storage channel. Our channel model incorporates the main features of DNA-based data storage. First, information is stored on many, short DNA strands. Second, the strands are stored in an unordered fashion inside the storage medium and each strand is rep

Andrey Kutuzov, Mario Giulianelli

We apply contextualised word embeddings to lexical semantic change detection in the SemEval-2020 Shared Task 1. This paper focuses on Subtask 2, ranking words by the degree of their semantic drift over time. We analyse the performance of two contextualising architectures (BERT and ELMo) and three change detection algorithms. We find that the most effective a

Jean Dolbeault, Gabriel Turinici

We study variants of the SEIR model for interpreting some qualitative features of the statistics of the Covid-19 epidemic in France. Standard SEIR models distinguish essentially two regimes: either the disease is controlled and the number of infected people rapidly decreases, or the disease spreads and contaminates a significant fraction of the population un

Sivasurya Santhanam

Long short-term memory(LSTM) units on sequence-based models are being used in translation, question-answering systems, classification tasks due to their capability of learning long-term dependencies. In Natural language generation, LSTM networks are providing impressive results on text generation models by learning language models with grammatically stable s

Christian Gilbertson, Eric B. Ford, Xavier Dumusque

Recent and upcoming stabilized spectrographs are pushing the frontier for Doppler spectroscopy to detect and characterize low-mass planets. Specifications for these instruments are so impressive that intrinsic stellar variability is expected to limit their Doppler precision for most target stars (Fischer et al. 2016). To realize their full potential, astrono

Andrew W. Mann, Marshall C. Johnson, Andrew Vanderburg, Adam L. Kraus

Exoplanets can evolve significantly between birth and maturity, as their atmospheres, orbits, and structures are shaped by their environment. Young planets ($<$1 Gyr) offer an opportunity to probe the critical early stages of this evolution, where planets evolve the fastest. However, most of the known young planets orbit prohibitively faint stars. We present

M. Smith, A. V. Andreev, B. Z. Spivak

We discuss a new mechanism of microwave absorption in s- and d-wave superconductors, which arises in the presence of a dc supercurrent in the system. It produces a contribution to the ac conductivity that is proportional to the inelastic quasiparticle relaxation time. This contribution also determines the supercurrent dependence of the conductivity. It may s

Massimo Frigerio, Claudio Destri, Stefano Olivares, Matteo G. A. Paris

Singularity or negativity of Glauber P-function is a widespread notion of nonclassicality, with important implications in quantum optics and with the character of an irreducible resource. Here we explore how P-nonclassicality may be generated by conditional Gaussian measurements on bipartite Gaussian states. This nonclassical steering may occur in a weak for

R. D. Pisarski, F. Rennecke, A. Tsvelik, S. Valgushev

We discuss the possibility of a Lifshitz regime, where the dispersion relation for Goldstone bosons and related fields has a minimum at nonzero momenta. Studies with the Functional Renormalization Group suggest that this occurs over a wide region in the plane of temperature and baryon chemical potential. Conversely, the FRG finds that the region in which flu

David Lomet, Chen Luo

A log structured store uses a single write I/O for a number of diverse and non-contiguous pages within a large buffer instead of using a write I/O for each page separately. This requires that pages be relocated on every write, because pages are never updated in place. Instead, pages are dynamically remapped on every write. Log structuring was invented for an

Georgios Bakirtzis, Garrett L. Ward, Christopher J. Deloglos, Carl R. Elks

Systems modeling practice lacks security analysis tools that can interface with modeling languages to facilitate security by design. Security by design is a necessity in the age of safety critical cyber-physical systems, where security violations can cause hazards. Currently, the overlap between security and safety is narrow. But deploying cyber-physical sys

Maharshi R. Pandya, Jessica Reyes, Bob Vanderheyden

Using author provided tags to predict tags for a new document often results in the overgeneration of tags. In the case where the author doesn't provide any tags, our documents face the severe under-tagging issue. In this paper, we present a method to generate a universal set of tags that can be applied widely to a large document corpus. Using IBM Watson's NL

F. Köttig, F. Tani, P. St. J. Russell

Gas-filled hollow-core photonic crystal fiber (PCF) is used for efficient nonlinear temporal compression of femtosecond laser pulses, two main schemes being direct soliton-effect self-compression, and spectral broadening followed by phase compensation. To obtain stable compressed pulses, it is crucial to avoid decoherence through modulational instability (MI

Tatsuma Yamaguchi, Yuichiro Matsuzaki, Soya Saijo, Hideyuki Watanabe

Nitrogen vacancy (NV) centers in diamonds is a promising system for quantum information processing and quantum sensing, and the control of the quantum state is essential for practical applications. In this study, we demonstrate a control of all the three transitions among the ground state sublevels of NV centers by applying external magnetic driving fields.

Sascha Meyen, Dorothee M. B. Sigg, Ulrike von Luxburg, Volker H. Franz

Background: It has repeatedly been reported that when making decisions under uncertainty, groups outperform individuals. In a lab setting, real groups are often replaced by simulated groups: Instead of performing an actual group discussion, individual responses are aggregated by a numerical computation. While studies typically use unweighted majority voting

Wenhan Xiong, Hong Wang, William Yang Wang

To extract answers from a large corpus, open-domain question answering (QA) systems usually rely on information retrieval (IR) techniques to narrow the search space. Standard inverted index methods such as TF-IDF are commonly used as thanks to their efficiency. However, their retrieval performance is limited as they simply use shallow and sparse lexical feat

Matteo Cimini, Emanuele Martelli, Matteo Bernardini

A delayed detached eddy simulation of a sub-scale cold-gas dual-bell nozzle flow at high Reynolds number and in sea-level mode is carried out at nozzle pressure ratio NPR=45.7. In this regime the over-expanded flow exhibits a symmetric and controlled flow separation at the inflection point, that is the junction between the two bells, leading to the generatio

Mohsen Mesgar, Edwin Simpson, Iryna Gurevych

Neural models for response generation produce responses that are semantically plausible but not necessarily factually consistent with facts describing the speaker's persona. These models are trained with fully supervised learning where the objective function barely captures factual consistency. We propose to fine-tune these models by reinforcement learning a

Sucharita Roy, Sourabh Bhattacharya

In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between global stationarity and nonstationarity for both parametric and nonparametric stochastic processes. Interestingly, our theory builds on our previous work on Bayesian characterizatio

Keith Tauscher, David Rapetti, Jack O. Burns

The assumptions inherent to global 21-cm signal analyses are rarely delineated. In this paper, we formulate a general list of suppositions underlying a given claimed detection of the global 21-cm signal. Then, we specify the form of these assumptions for two different analyses: 1) the one performed by the EDGES team showing an absorption trough in brightness

Firoj Alam, Shaden Shaar, Fahim Dalvi, Hassan Sajjad

With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic has been declared one of the most important focus areas of the World Health Organization, with dangers ranging from promoting fake cures, rum

Will M. Farr, Katerina Chatziioannou

Galactic double neutron star systems have a tight mass distribution around $\sim 1.35 M_{\odot}$, but the mass distribution of all known pulsars is broader. Here we reconstruct the Alsing, et al. (2018) bimodal mass distribution of pulsars observed in binary systems, incorporating data from observations of J0740+6620 which were not available at the time of t

Xiaoran Chen, Suhang You, Kerem Can Tezcan, Ender Konukoglu

Unsupervised lesion detection is a challenging problem that requires accurately estimating normative distributions of healthy anatomy and detecting lesions as outliers without training examples. Recently, this problem has received increased attention from the research community following the advances in unsupervised learning with deep learning. Such advances

Mónica Benito, Guido Burkard

Superconducting quantum devices provide excellent connectivity and controllability while semiconductor spin qubits stand out with their long-lasting quantum coherence, fast control, and potential for miniaturization and scaling. In the last few years, remarkable progress has been made in combining superconducting circuits and semiconducting devices into hybr

Kade Head-Marsden, Stefan Krastanov, David A. Mazziotti, Prineha Narang

With the rapid progress in quantum hardware, there has been an increased interest in new quantum algorithms to describe complex many-body systems searching for the still-elusive goal of 'useful quantum advantage'. Surprisingly, quantum algorithms for the treatment of open quantum systems (OQSs) have remained under-explored, in part due to the inherent challe

C. Hati, J. Kriewald, J. Orloff, A. M. Teixeira

Motivated by a simultaneous explanation of the apparent discrepancies in the light charged lepton anomalous magnetic dipole moments, and the anomalous internal pair creation in $^8$Be nuclear transitions, we explore a simple New Physics model, based on an extension of the Standard Model gauge group by a $U(1)_{B-L}$. The model further includes heavy vector-l

Eric Mascot, Jasmin Bedow, Martin Graham, Stephan Rachel

Atomic manipulation and interface engineering techniques have provided a novel approach to custom-designing topological superconductors and the ensuing Majorana zero modes, representing a new paradigm for the realization of topological quantum computing and topology-based devices. Magnet-superconductor hybrid (MSH) systems have proven to be experimentally su

Moiya McTier, David Kipping, Kathryn Johnston

The Galactic bulge is a tumultuous dense region of space, packed with stars separated by far smaller distances than those in the Solar neighborhood. A quantification of the frequency and proximity of close stellar encounters in this environment dictates the exchange of material, disruption of planetary orbits, and threat of sterilizing energetic events. We p

M. Spavone, E. Iodice, G. van de Ven, J. Falcón-Barroso

This work is based on deep multi-band (g, r, i) data from the Fornax Deep Survey with VST. We analyse the surface brightness profiles of the 19 bright ETGs inside the virial radius of the Fornax cluster. The main aim of this work is to identify signatures of accretion onto galaxies by studying the presence of outer stellar halos, and understand their nature

Sanjib Sabhapandit, Satya N. Majumdar

We study the decay rate $\theta(a)$ that characterizes the late time exponential decay of the first-passage probability density $F_a(t|0) \sim e^{-\theta(a)\, t}$ of a diffusing particle in a one dimensional confining potential $U(x)$, starting from the origin, to a position located at $a>0$. For general confining potential $U(x)$ we show that $\theta(a)$, a

Chase Kimball, Colm Talbot, Christopher P. L. Berry, Matthew Carney

In dense stellar environments, the merger products of binary black hole mergers may undergo additional mergers. These hierarchical mergers are predicted to have higher masses than the first generation of black holes made from stars. The components of hierarchical mergers are expected to have significant characteristic spins $\chi\sim 0.7$. However, since the

Zi-Jian Lang, Ruoshi Jiang, Wei Ku

The families of high-temperature superconductors recently welcomed a new member: hole doped nickelate Nd$_{0.8}$Sr$_{0.2}$NiO$_2$ with a $\sim$15K transition temperature. To understand its emergent low-energy behaviors and experimental properties, an immediate key question is whether the superconducting hole carriers reside in oxygen as in the cuprates, or i

Hao Geng

We study holographic entanglement and information scrambling in de-Sitter (dS) space in the context of the DS/dS correspondence. We find that our previously identified non-local entanglement structure of dS vacua can be extended out of the time-reflection symmetric slice. We extend the geometry to a two-sided configuration and calculate the zero-time mutual

Jorge Miguel-Ramiro, Alexander Pirker, Wolfgang Dür

We show how to make quantum networks, both standard and entanglement-based, genuine quantum by providing them with the possibility of handling superposed tasks and superposed addressing. This extension of their functionality relies on a quantum control register, which specifies not only the task of the network, but also the corresponding weights in a coheren

Michael A. Lepori, Tal Linzen, R. Thomas McCoy

Sequence-based neural networks show significant sensitivity to syntactic structure, but they still perform less well on syntactic tasks than tree-based networks. Such tree-based networks can be provided with a constituency parse, a dependency parse, or both. We evaluate which of these two representational schemes more effectively introduces biases for syntac

C. Adam, K. Oles, A. Wereszczynski

We consider a version of the Skyrme model where both the kinetic term and the Skyrme term are multiplied by field-dependent coupling functions. For suitable choices, this "dielectric Skyrme model" has static solutions saturating the pertinent topological bound in the sector of baryon number (or topological charge) $B=\pm 1$ but not for higher $|B|$. This imp

Yutaka Fujita, Hiroshi Nagai. Takuya Akahori, Akiko Kawachi, Atsuo T. Okazaki

We report Atacama Large Millimeter/submillimeter Array (ALMA) observations of the gamma-ray binary system containing the pulsar PSR B1259-63 orbiting around a massive star LS 2883 in an inactive period between the 2017 and 2021 periastron passages. We detected radio continuum emission from the binary system at 97 GHz (Band 3) and 343 GHz (Band 7). Compared w

Upamanyu Moitra, Sunil Kumar Sake, Sandip P. Trivedi

We analyse near-extremal black brane configurations in asymptotically $\mathrm{AdS}_4$ spacetime with the temperature $T$, chemical potential $\mu$, and three-velocity $u^\nu$, varying slowly. We consider a low-temperature limit where the rate of variation is much slower than $\mu$, but much bigger than $T$. This limit is different from the one considered fo

Ricardo Cepedello, Martin Hirsch, Paulina Rocha-Morán, Avelino Vicente

We study charged lepton flavor violation for the three most popular 3-loop Majorana neutrino mass models. We call these models "minimal" since their particle content correspond to the minimal sets for which genuine 3-loop models can be constructed. In all the three minimal models the neutrino mass matrix is proportional to some powers of Standard Model lepto

G. Traven, S. Feltzing, T. Merle, M. Van der Swaelmen

Binary stellar systems form a large fraction of the Galaxy's stars. They are useful as laboratories for studying the physical processes taking place within stars, and must be correctly taken into account when observations of stars are used to study the structure and evolution of the Galaxy. We present a sample of 12760 well-characterised double-lined spectro

Aaron C. Rizzuto, Elisabeth R. Newton, Andrew W. Mann, Benjamin M. Tofflemire

We present the discovery of a transiting hot Jupiter orbiting HIP 67522 ($T_{eff}\sim5650$ K; $M_* \sim 1.2 M_{\odot}$) in the 10-20 Myr old Sco-Cen OB association. We identified the transits in the TESS data using our custom notch-filter planet search pipeline, and characterize the system with additional photometry from Spitzer, spectroscopy from SOAR/Goodm

Luca Di Luzio

I discuss the implementation of the Peccei-Quinn mechanism in a minimal realization of the Pati-Salam partial unification scheme. The axion mass is shown to be related to the Pati-Salam breaking scale and it is predicted via a two-loop renormalization group analysis to be in the window $m_a \in [10^{-11}, \, 3 \times 10^{-7}]$ eV, as a function of a sliding

Hamidreza Kazemi, Sebastian Eggert, Nicholas Sedlmayr

Use of a spin polarized current for the manipulation of magnetic domain walls in ferromagnetic nanowires has been the subject of intensive research for many years. Recently, due to technological advancements, creating nano-contacts with special characteristics is becoming more and more prevalent. We now present a full quantum investigation of the magnetoresi

Gautam Kamath, Jonathan Ullman

Differentially private statistical estimation has seen a flurry of developments over the last several years. Study has been divided into two schools of thought, focusing on empirical statistics versus population statistics. We suggest that these two lines of work are more similar than different by giving examples of methods that were initially framed for emp

A. J. Mead, T. Tröster, C. Heymans, L. Van Waerbeke

On the scale of galactic haloes, the distribution of matter in the cosmos is affected by energetic, non-gravitational processes; so-called baryonic feedback. A lack of knowledge about the details of how feedback processes redistribute matter is a source of uncertainty for weak-lensing surveys, which accurately probe the clustering of matter in the Universe o

Hao-Lin Li, Zhe Ren, Jing Shu, Ming-Lei Xiao

We present a complete list of the dimension 8 operator basis in the standard model effective field theory using group theoretic techniques in a systematic and automated way. We adopt a new form of operators in terms of the irreducible representations of the Lorentz group, and identify the Lorentz structures as states in a $SU(N)$ group. In this way, redundan

Piet Lammers, Martin Tassy

The motivation for this article is to derive strict convexity of the surface tension for Lipschitz random surfaces, that is, for models of random Lipschitz functions from $\mathbb Z^d$ to $\mathbb Z$ or $\mathbb R$. An essential innovation is that random surface models with long- and infinite-range interactions are included in the analysis. More specifically

Niklas Garner, Oscar Kivinen

We show that Hilbert schemes of planar curve singularities and their parabolic variants can be interpreted as certain generalized affine Springer fibers for $GL_n$, as defined by Goresky-Kottwitz-MacPherson. Using a generalization of affine Springer theory for Braverman-Finkelberg-Nakajima's Coulomb branch algebras, we construct a rational Cherednik algebra

Juste Raimbault

The dynamics of urban systems can be understood from an evolutionary perspective, in some sense extending biological and cultural evolution. Models for systems of cities implementing elementary evolutionary processes remain however to be investigated. We propose here such a model for urban dynamics at the macroscopic scale, in which the diffusion of innovati

Yang-Zhi Chou, Fengcheng Wu, Sankar Das Sarma

We theoretically study the Hofstadter butterfly of a triangular network model in minimally twisted bilayer graphene (mTBLG). The band structure manifests periodicity in energy, mimicking that of Floquet systems. The butterfly diagrams provide fingerprints of the model parameters and reveal the hidden band topology. In a strong magnetic field, we establish th

Xuan Luo, Jia-Bin Huang, Richard Szeliski, Kevin Matzen

We present an algorithm for reconstructing dense, geometrically consistent depth for all pixels in a monocular video. We leverage a conventional structure-from-motion reconstruction to establish geometric constraints on pixels in the video. Unlike the ad-hoc priors in classical reconstruction, we use a learning-based prior, i.e., a convolutional neural netwo

Zarana Parekh, Jason Baldridge, Daniel Cer, Austin Waters

By supporting multi-modal retrieval training and evaluation, image captioning datasets have spurred remarkable progress on representation learning. Unfortunately, datasets have limited cross-modal associations: images are not paired with other images, captions are only paired with other captions of the same image, there are no negative associations and there

Tohid Farajollahpour, S. A. Jafari

In planar tilted Dirac cone systems, the tilt parameter can be made space-dependent by either a perpendicular displacement field, or by chemical substitution in certain systems. We show that the symmetric partial derivative of the tilt parameter generates non-Abelian synthetic gauge fields in these systems. The small velocity limit of these gauge forces corr

Maria Chikina, Wesley Pegden

We discuss the failure of monotonicity properties for even simple compartmental epidemic models, for the case where transmission rates are non-constant. We also identify a special case in which monotonicity holds.

Hanrui Wang, Kuan Wang, Jiacheng Yang, Linxiao Shen

Automatic transistor sizing is a challenging problem in circuit design due to the large design space, complex performance trade-offs, and fast technological advancements. Although there has been plenty of work on transistor sizing targeting on one circuit, limited research has been done on transferring the knowledge from one circuit to another to reduce the

Hing Ong, Paul E. Roundy

This study derives a complete set of equatorially confined wave solutions from an anelastic equation set with the complete Coriolis terms, which include both the vertical and meridional planetary vorticity. The propagation mechanism can change with the effective static stability. When the effective static stability reduces to neutral, buoyancy ceases, but th

Anna Breit, Artem Revenko, Kiamehr Rezaee, Mohammad Taher Pilehvar

We present WiC-TSV, a new multi-domain evaluation benchmark for Word Sense Disambiguation. More specifically, we introduce a framework for Target Sense Verification of Words in Context which grounds its uniqueness in the formulation as a binary classification task thus being independent of external sense inventories, and the coverage of various domains. This

Eric Wallace, Mitchell Stern, Dawn Song

Adversaries may look to steal or attack black-box NLP systems, either for financial gain or to exploit model errors. One setting of particular interest is machine translation (MT), where models have high commercial value and errors can be costly. We investigate possible exploits of black-box MT systems and explore a preliminary defense against such threats.

Siddhartha Gairola, Mayur Hemani, Ayush Chopra, Balaji Krishnamurthy

Few-shot segmentation (FSS) methods perform image segmentation for a particular object class in a target (query) image, using a small set of (support) image-mask pairs. Recent deep neural network based FSS methods leverage high-dimensional feature similarity between the foreground features of the support images and the query image features. In this work, we

Lingfeng Li, Ying-Ying Li, Tao Liu, Si-Jun Xu

Information deformation and loss in jet clustering are one of the major limitations for precisely measuring hadronic events at future $e^-e^+$ colliders. Because of their dominance in data, the measurements of such events are crucial for advancing the precision frontier of Higgs and electroweak physics in the next decades. We show that this difficulty can be

Rohan Jha, Charles Lovering, Ellie Pavlick

Neural models often exploit superficial features to achieve good performance, rather than deriving more general features. Overcoming this tendency is a central challenge in areas such as representation learning and ML fairness. Recent work has proposed using data augmentation, i.e., generating training examples where the superficial features fail, as a means

Isabel Cachola, Kyle Lo, Arman Cohan, Daniel S. Weld

We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge and understanding of complex domain-specific language. To facilitate study on this task, we introduce SciTLDR, a new multi-target dataset of 5.4K TLDRs over 3.2K papers. SciTLDR co

Cesar A. Agón, Sagar F. Lokhande, Juan F. Pedraza

Quantum corrections to the entanglement entropy of matter fields interacting with dynamical gravity have proven to be very important in the study of the black hole information problem. We consider a one-particle excited state of a massive scalar field infalling in a pure AdS$_3$ geometry and compute these corrections for bulk subregions anchored on the AdS b

Anurag Anshu, Aram W. Harrow, Mehdi Soleimanifar

In this work, we make a connection between two seemingly different problems. The first problem involves characterizing the properties of entanglement in the ground state of gapped local Hamiltonians, which is a central topic in quantum many-body physics. The second problem is on the quantum communication complexity of testing bipartite states with EPR assist

Nelson F. Liu, Daniel Hershcovich, Michael Kranzlein, Nathan Schneider

In lexical semantics, full-sentence segmentation and segment labeling of various phenomena are generally treated separately, despite their interdependence. We hypothesize that a unified lexical semantic recognition task is an effective way to encapsulate previously disparate styles of annotation, including multiword expression identification / classification

Julius Eckhard, Sakura Schafer-Nameki, Yi-Nan Wang

The trinions $T_N$ are a class of 5d $\mathcal{N}=1$ superconformal field theories (SCFTs) realized as M-theory on $\mathbb{C}^3/\mathbb{Z}_N \times \mathbb{Z}_N$. We apply to $T_N$, as well as closely-related SCFTs that are obtained by mass deformations, a multitude of recently developed approaches to studying 5d SCFTs and their IR gauge theory descriptions

Mihir Kale, Abhinav Rastogi

Virtual assistants such as Google Assistant, Amazon Alexa, and Apple Siri enable users to interact with a large number of services and APIs on the web using natural language. In this work, we investigate two methods for Natural Language Generation (NLG) using a single domain-independent model across a large number of APIs. First, we propose a schema-guided a

Ruchi Guo

Immersed finite element (IFE) methods are a group of long-existing numerical methods for solving interface problems on unfitted meshes. A core argument of the methods is to avoid mesh regeneration procedure when solving moving interface problems. Despite the various applications in moving interface problems, a complete theoretical study on the convergence be

Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park

Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first step due to the complexity of understanding and applying deep learning. We present CNN Explainer, an interactive visualization tool designed for non-experts to learn and examine co

Sho Yokoi, Ryo Takahashi, Reina Akama, Jun Suzuki

A key principle in assessing textual similarity is measuring the degree of semantic overlap between two texts by considering the word alignment. Such alignment-based approaches are intuitive and interpretable; however, they are empirically inferior to the simple cosine similarity between general-purpose sentence vectors. To address this issue, we focus on an

Glenn Barnich, Pujian Mao, Romain Ruzziconi

We derive the expressions for the local, on-shell closed co-dimension 2 forms in the Palatini formulation of general relativity and explicitly show their on-shell equivalence to those of the metric formulation. When compared to other first order formulations, two subtleties have to be addressed during the construction: off-shell non-metricity and the fact th

Phillip Keung, Yichao Lu, Julian Salazar, Vikas Bhardwaj

Multilingual contextual embeddings have demonstrated state-of-the-art performance in zero-shot cross-lingual transfer learning, where multilingual BERT is fine-tuned on one source language and evaluated on a different target language. However, published results for mBERT zero-shot accuracy vary as much as 17 points on the MLDoc classification task across fou

John Ryan Westernacher-Schneider

A neutron star in a compact binary is expected to be well-approximated by a barotropic flow during the inspiral phase. During the merger phase, where tidal disruption and shock-heating occur, a baroclinic description is needed instead. In the barotropic case, a Hamiltonian formulation potentially offers unique benefits for numerical relativity simulations of

Ilia Kuznetsov, Iryna Gurevych

Deep pre-trained contextualized encoders like BERT (Delvin et al., 2019) demonstrate remarkable performance on a range of downstream tasks. A recent line of research in probing investigates the linguistic knowledge implicitly learned by these models during pre-training. While most work in probing operates on the task level, linguistic tasks are rarely unifor

Justin Hilburn, Joel Kamnitzer, Alex Weekes

Given a representation N of a reductive group G, Braverman-Finkelberg-Nakajima have defined a remarkable Poisson variety called the Coulomb branch. Their construction of this space was motivated by considerations from 3d gauge theories and symplectic duality. The coordinate ring of this Coulomb branch is defined as a convolution algebra, using a vector bundl

Kazumasa Nomura, Paul Terwilliger

In this paper we introduce the notion of an idempotent system. This linear algebraic object is motivated by the structure of an association scheme. We focus on a family of idempotent systems, said to be symmetric. A symmetric idempotent system is an abstraction of the primary module for the subconstituent algebra of a symmetric association scheme. We describ

He Bai, Peng Shi, Jimmy Lin, Yuqing Xie

Transformers are powerful for sequence modeling. Nearly all state-of-the-art language models and pre-trained language models are based on the Transformer architecture. However, it distinguishes sequential tokens only with the token position index. We hypothesize that better contextual representations can be generated from the Transformer with richer position

Hao Zheng, Andrew Price, Chris Myers

The enormous number of states reachable during explicit model checking is the main bottleneck for scalability. This paper presents approaches of using decision diagrams to represent very large state space compactly and efficiently. This is possible for asynchronous systems as two system states connected by a transition often share many same local portions. U

Sean D Lawley

Anomalous subdiffusion characterizes transport in diverse physical systems and is especially prevalent inside biological cells. In cell biology, the prevailing model for chemical activation rates has recently changed from the first passage time (FPT) of a single searcher to the FPT of the fastest searcher out of many searchers to reach a target, which is cal

Camilla Jacome, Michael Monteiro, Miguel Cabral, Pedro Carvalho

The process of neighborhood establishment in an IPv6 network is made out through the NDP (Neighbor Discovery Protocol). Using ICMPv6 messages (NS - Neighbor Solicitation and NA - Neighbor Advertisement) which contains the IP address to be resolved, is exposed during the exchange of messages, making communication vulnerable to various types of attacks. This p

Nicola De Cao, Michael Schlichtkrull, Wilker Aziz, Ivan Titov

Attribution methods assess the contribution of inputs to the model prediction. One way to do so is erasure: a subset of inputs is considered irrelevant if it can be removed without affecting the prediction. Though conceptually simple, erasure's objective is intractable and approximate search remains expensive with modern deep NLP models. Erasure is also susc

Kristjan Ottar Klausen, Anna Sitek, Sigurdur I. Erlingsson, Andrei Manolescu

The effects of geometry on the hosting of Majorana zero modes are explored in core-shell nanowires with a hexagonal core and a triangular shell, and vice versa. The energy interval separating electronic states localized in the corners from states localized on the sides of the shell is shown to be larger for a triangular nanowire with a hexagonal core, than a

Chen Zhou, Cheng-Yu Wang, Zhiwen Liu

A deep learning based non-line-of-sight (NLOS) imaging system is developed to image an occluded object off a scattering surface. The neural net is trained using only handwritten digits, and yet exhibits capability to reconstruct patterns distinct from the training set, including physical objects. It can also reconstruct a cartoon video from its scattering pa

Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto

Learning from visual observations is a fundamental yet challenging problem in Reinforcement Learning (RL). Although algorithmic advances combined with convolutional neural networks have proved to be a recipe for success, current methods are still lacking on two fronts: (a) data-efficiency of learning and (b) generalization to new environments. To this end, w

Rachel Bawden, Biao Zhang, Lisa Yankovskaya, Andre Tättar

We investigate a long-perceived shortcoming in the typical use of BLEU: its reliance on a single reference. Using modern neural paraphrasing techniques, we study whether automatically generating additional diverse references can provide better coverage of the space of valid translations and thereby improve its correlation with human judgments. Our experiment

D. Pugliese, G. Montani

This work discusses observational evidences of quantum effects on geometry in a black hole (BH) astrophysical context. We study properties of a family of loop quantum corrected regular BH solutions and their horizons, focusing on the geometry symmetries. We explore a recent model where the geometry is determined by a metric quantum modification outside the h

Sascha Meyen, Iris A. Zerweck, Catarina Amado, Ulrike von Luxburg

Current literature holds that many cognitive functions can be performed outside consciousness. Evidence for this view comes from unconscious priming. In a typical experiment, visual stimuli are masked, such that participants are close to chance when directly asked to which of two categories the stimuli belong. This close-to-zero sensitivity is seen as eviden

Hua Sun

The compound secure groupcast problem is considered, where the key variables at $K$ receivers are designed so that a transmitter can securely groupcast a message to any $N$ out of the $K$ receivers through a noiseless broadcast channel. The metric is the information theoretic tradeoff between key storage $\alpha$, i.e., the number of bits of the key variable

Georgios Antoniou, Lorenzo Bordin, Thomas P. Sotiriou

We demonstrate that there are theories that exhibit spontaneous scalarization in the strong gravity regime while having General Relativity with a constant scalar as a cosmological attractor. We identify the minimal model that has this property and discuss its extensions.

Sridhar Tripathy, Subhendu Das, Jaydeep Datta, Nayana Majumdar

This work reports a cost-effective, simple front-end readout and DAQ of a RPC-based muon scattering tomography system under construction. The Time-over-threshold property of NINO ASICs has been exploited to achieve precise tracking by extraction of position information. The use of a low-cost FPGA for event selection and TOT measurement has been demonstrated

Giuseppe Russo, Nora Hollenstein, Claudiu Musat, Ce Zhang

We introduce CGA, a conditional VAE architecture, to control, generate, and augment text. CGA is able to generate natural English sentences controlling multiple semantic and syntactic attributes by combining adversarial learning with a context-aware loss and a cyclical word dropout routine. We demonstrate the value of the individual model components in an ab

Arkadiusz Kuroś, Rick Mukherjee, Weronika Golletz, Frederic Sauvage

A remarkable consequence of spontaneously breaking the time translational symmetry in a system, is the emergence of time crystals. In periodically driven systems, discrete time crystals (DTC) can be realized which have a periodicity that is n times the driving period. However, all of the experimental observations have been performed for period-doubling and p

P. O. Sukhachov, E. V. Gorbar

The superconducting s-wave state in Weyl semimetals in a strong strain-induced pseudomagnetic field is investigated in a model with local four-fermion interaction. It is found that only the inter-node pairing is possible in the lowest pseudo-Landau level approximation. Unlike the case of the lowest Landau level in a conventional magnetic field, the correspon

Scott Lawrence, Zeeve Rogoszinski

A recent proposal for the detection of a hypothetical gravitating body 500 AU from the Sun (termed Planet 9) calls for a fleet of near-relativistic spacecraft, equipped with high-precision clocks, to be sent to a region where the object is suspected to be. We show that the technological constraints of such a mission can be relaxed somewhat, while improving t

Yehudit Meged, Avi Caciularu, Vered Shwartz, Ido Dagan

We study the potential synergy between two different NLP tasks, both confronting predicate lexical variability: identifying predicate paraphrases, and event coreference resolution. First, we used annotations from an event coreference dataset as distant supervision to re-score heuristically-extracted predicate paraphrases. The new scoring gained more than 18