arXiv subjects

Xin Xu

Publications and source records attributed to Xin Xu.

At least 235 records · Page 13Linked to original sources

arXiv2023

LAMBADA: Backward Chaining for Automated Reasoning in Natural Language

Remarkable progress has been made on automated reasoning with natural text, by using Language Models (LMs) and methods such as Chain-of-Thought and Selection-Inference. These techniques search for proofs in the forward direction from axioms to the conclusion, which suffers from a combinatorial explosion of the search space, and thus high failure rates for problems requiring longer chains of reasoning. The classical automated reasoning literature has shown that reasoning in the backward direction (i.e. from the intended conclusion to supporting axioms) is significantly more efficient at proof-finding. Importing this intuition into the LM setting, we develop a Backward Chaining algorithm, called LAMBADA, that decomposes reasoning into four sub-modules. These sub-modules are simply implemented by few-shot prompted LM inference. We show that LAMBADA achieves sizable accuracy boosts over state-of-the-art forward reasoning methods on challenging logical reasoning datasets, particularly when deep and accurate proof chains are required.

cs.AI↗

arXiv2023

Dr.ICL: Demonstration-Retrieved In-context Learning

In-context learning (ICL), teaching a large language model (LLM) to perform a task with few-shot demonstrations rather than adjusting the model parameters, has emerged as a strong paradigm for using LLMs. While early studies primarily used a fixed or random set of demonstrations for all test queries, recent research suggests that retrieving semantically similar demonstrations to the input from a pool of available demonstrations results in better performance. This work expands the applicability of retrieval-based ICL approaches by demonstrating that even simple word-overlap similarity measures such as BM25 outperform randomly selected demonstrations. Furthermore, we extend the success of retrieval-based ICL to instruction-finetuned LLMs as well as Chain-of-Thought (CoT) prompting. For instruction-finetuned LLMs, we find that although a model has already seen the training data at training time, retrieving demonstrations from the training data at test time yields better results compared to using no demonstrations or random demonstrations. Last but not least, we train a task-specific demonstration retriever that outperforms off-the-shelf retrievers.

cs.CL↗

arXiv2023

$B_c^- \to J/ψ(\to μ^+ μ^-)τ^- (\to π^- ν_τ, ρ^- ν_τ, \ell^-\barν_\ellν_τ)\barν_τ$ decays with visible final-state kinematics

The semitauonic $B_c^- \to J/ψτ^-\barν_τ$ decay is optimal to scrutinize possible new physics effects in $b \to c τ^- \barν_τ$ transitions as indicated by the current data on $R(D^{(*)})$ anomalies. In this work, we study the $B_c^- \to J/ψτ^-\barν_τ$ decay with both polarized $τ$ and $J/ψ$. Their subsequent decays, with $J/ψ\to μ^+ μ^-$ as well as $τ^- \to π^- ν_τ$, $τ^- \to ρ^- ν_τ$ and $τ^- \to \ell^-\barν_\ellν_τ$, are exploited to extract the energy and angular distributions of the charged final-state particles in the processes. Starting with the most general effective Hamiltonian relevant for the $b \to c τ^- \barν_τ$ transitions, including all possible Lorentz structures of the dimension-six operators with both left- and right-handed neutrinos, we first derive the five-fold differential decay rate in terms of the visible final-state kinematics. From this distribution, we then construct in total 34 normalized observables, among which nine refer to the CP-violating triple product asymmetries that vanish within the Standard Model. We also construct five new observables based on the combinations of these normalized observables that can only be attributed to the right-handed neutrinos. On the other hand, considering the low statistics of the fully differential distribution, we introduce some integrated observables with only one kinematic variable left, which are more promising to be measured due to the largely increased statistics. The sensitivities of all these observables to the different new physics scenarios are investigated in detail. Finally, assuming an ideal circumstance, we give an estimate of the statistical uncertainties of the nine CP-conserving observables at LHCb and found that $τ^-\to π^-ν_τ$ has the highest analyzing power among the three $τ$ decay channels.

hep-ph↗

arXiv2023

Prokaryotic genome editing based on the subtype I-B-Svi CRISPR-Cas system

Type I CRISPR-Cas systems are the most common among six types of CRISPR-Cas systems, however, non-self-targeting genome editing based on a single Cas3 of type I CRISPR-Cas systems has not been reported. Here, we present the subtype I-B-Svi CRISPR-Cas system (with three confirmed CRISPRs and a cas gene cluster) and genome editing based on this system found in Streptomyces virginiae IBL14. Importantly, like the animal-derived bacterial protein SpCas9 (1368 amino-acids), the single, compact, non-animal-derived bacterial protein SviCas3 (771 amino-acids) can also direct template-based microbial genome editing through the target cell's own homology-directed repair system, which breaks the view that the genome editing based on type I CRISPR-Cas systems requires a full Cascade. Notably, no off-target changes or indel-formation were detected in the analysis of potential off-target sites. This discovery broadens our understanding of the diversity of type I CRISPR-Cas systems and will facilitate new developments in genome editing tools.

q-bio.GN↗

arXiv2023

Pulsar and Magnetar Navigation with Fermi/GBM and GECAM

The determination of the absolute and relative position of a spacecraft is critical for its operation, observations, data analysis, scientific studies, as well as deep space exploration in general. A spacecraft that can determine its own absolute position autonomously may perform more than that must rely on transmission solutions. In this work, we report an absolute navigation accuracy of $\sim$ 20 km using 16-day Crab pulsar data observed with $Fermi$ Gamma ray Burst Monitor (GBM). In addition, we propose a new method with the inverse process of the triangulation for joint navigation using repeated bursts like that from the magnetar SGR J1935+2154 observed by the Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) and GBM.

astro-ph.IM↗

arXiv2023

The Monge-Ampère equation for $(n-1)$-quaternionic PSH functions on a hyperKähler manifold

We prove the existence of unique smooth solutions to the quaternionic Monge-Ampère equation for $(n-1)$-quaternionic plurisubharmonic functions on a hyperKähler manifold and thus obtain solutions for the quaternionic form type equation. We derive $C^0$ estimate by establishing a Cherrier-type inequality as in Tosatti and Weinkove [22]. By adopting the approach of Dinew and Sroka [9] to our context, we obtain $C^1$ and $C^2$ estimates without assuming the flatness of underlying hyperKähler metric comparing to previous results [14].

math.DG↗

arXiv2022

RDP-Net: Region Detail Preserving Network for Change Detection

Change detection (CD) is an essential earth observation technique. It captures the dynamic information of land objects. With the rise of deep learning, convolutional neural networks (CNN) have shown great potential in CD. However, current CNN models introduce backbone architectures that lose detailed information during learning. Moreover, current CNN models are heavy in parameters, which prevents their deployment on edge devices such as UAVs. In this work, we tackle this issue by proposing RDP-Net: a region detail preserving network for CD. We propose an efficient training strategy that constructs the training tasks during the warmup period of CNN training and lets the CNN learn from easy to hard. The training strategy enables CNN to learn more powerful features with fewer FLOPs and achieve better performance. Next, we propose an effective edge loss that increases the penalty for errors on details and improves the network's attention to details such as boundary regions and small areas. Furthermore, we provide a CNN model with a brand new backbone that achieves the state-of-the-art empirical performance in CD with only 1.70M parameters. We hope our RDP-Net would benefit the practical CD applications on compact devices and could inspire more people to bring change detection to a new level with the efficient training strategy. The code and models are publicly available at https://github.com/Chnja/RDPNet.

eess.IV↗

arXiv2022

The ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge (ICSRC): Dataset, Tracks, Baseline and Results

This paper summarizes the outcomes from the ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge (ICSRC). We first address the necessity of the challenge and then introduce the associated dataset collected from a new-energy vehicle (NEV) covering a variety of cockpit acoustic conditions and linguistic contents. We then describe the track arrangement and the baseline system. Specifically, we set up two tracks in terms of allowed model/system size to investigate resource-constrained and -unconstrained setups, targeting to vehicle embedded as well as cloud ASR systems respectively. Finally we summarize the challenge results and provide the major observations from the submitted systems.

cs.SD↗

arXiv2022

Simulation of Transients in Natural Gas Networks via A Semi-analytical Solution Approach

Simulation and control of the transient flow in natural gas networks involve solving partial differential equations (PDEs). This paper proposes a semi-analytical solutions (SAS) approach for fast and accurate simulation of the natural gas transients. The region of interest is divided into a grid, and an SAS is derived for each grid cell in the form of the multivariate polynomials, of which the coefficients are identified according to the initial value and boundary value conditions. The solutions are solved in a ``time-stepping'' manner; that is, within one time step, the coefficients of the SAS are identified and the initial value of the next time step is evaluated. This approach achieves a much larger grid cell than the widely used finite difference method, and thus enhances the computational efficiency significantly. To further reduce the computation burden, the nonlinear terms in the model are simplified, which induces another SAS scheme that can greatly reduce the time consumption and have minor impact on accuracy. The simulation results on a single pipeline case and a 6-node network case validate the advantages of the proposed SAS approach in accuracy and computational efficiency.

math.DS↗

arXiv2022

An approximation to the invariant measure of the limiting diffusion of G/Ph/n+GI queues in the Halfin-Whitt regime and related asymptotics

In this paper, we develop a stochastic algorithm based on the Euler--Maruyama scheme to approximate the invariant measure of the limiting multidimensional diffusion of $G/Ph/n+GI$ queues in the Halfin-Whitt regime. Specifically, we prove a non-asymptotic error bound between the invariant measures of the approximate model from the algorithm and the limiting diffusion. To establish the error bound, we employ the recently developed Stein's method for multi-dimensional diffusions, in which the regularity of Stein's equation developed by Gurvich (2014, 2022) plays a crucial role. We further prove the central limit theorem (CLT) and the moderate deviation principle (MDP) for the occupation measures of the limiting diffusion of $G/Ph/n+GI$ queues and its Euler-Maruyama scheme. In particular, the variances in the CLT and MDP associated with the limiting diffusion are determined by Stein's equation and Malliavin calculus, in which properties of a mollified diffusion and an associated weighted occupation time play a crucial role.

math.PR↗

arXiv2022

Polarization effects on fluorescence emission of zebrafish neurons using light-sheet microscopy

Light-sheet fluorescence microscopy (LSFM) makes use of a thin plane of light to optically section and image transparent tissues or organisms {\it{in vivo}}, which has the advantages of fast imaging speed and low phototoxicity. In this paper, we have employed light-sheet microscopy to investigate the polarization effects on fluorescence emission of zebrafish neurons via modifying the electric oscillation orientation of the excitation light. The intensity of the fluorescence emission from the excited zebrafish larvae follows a cosine square function with respect to the polarization state of the excitation light and reveals a 40$\%$ higher fluorescence emission when the polarization orientation is orthogonal to the illumination and detection axes. Through registration and subtraction of fluorescence images under different polarization states, we have demonstrated that most of the enhanced fluorescence signals are from the nerve cells rather than the extracellular substance. This provides us a way to distinguish the cell boundaries and observe the organism structures with improved contrast and resolution.

physics.bio-ph↗

arXiv2022

Singular Limits for the Navier-Stokes-Poisson Equations of Viscous Plasma with Strong Density Boundary Layer

The quasi-neutral limit of the Navier-Stokes-Poisson system modeling a viscous plasma with vanishing viscosity coefficients in the half-space $\mathbb{R}^{3}_{+}$ is rigorously proved under a Navier-slip boundary condition for velocity and the Dirichlet boundary condition for electric potential. This is achieved by establishing the nonlinear stability of the approximation solutions involving the strong boundary layer in density and electric potential, which comes from the break-down of the quasi-neutrality near the boundary, and dealing with the difficulty of the interaction of this strong boundary layer with the weak boundary layer of the velocity field.

math.AP↗

arXiv2022

Laboratory development of a heterodyne interferometric system for translation and tilt measurement of the proof mass in the space gravitational wave detection

Laser heterodyne interferometry plays a key role in the proof mass's monitor and control by measuring its multiple degrees of freedom motions in the Space Gravitational Wave Detection. Laboratory development of polarization-multiplexing heterodyne interferometer (PMHI) using quadrant photodetectors (QPD) is presented in this paper, intended for measuring the translation and tilt of a proof mass. The system is of symmetric design, which can expand to five degrees of freedom measurements based on polarization-multiplexing and differential wavefront sensing (DWS). The ground-simulated experimental results demonstrate that a measurement noise of 3 pm/Hz$^{1/2}$ and 2 nrad/Hz$^{1/2}$ at 1 Hz have been achieved respectively. The tilt-to-length error is dominated by geometric misalignment for the current system, the coupling of which is at micrometer level within a tilt range of 1000 μrad.

astro-ph.IM↗

arXiv2022

Towards Generalizable Person Re-identification with a Bi-stream Generative Model

Generalizable person re-identification (re-ID) has attracted growing attention due to its powerful adaptation capability in the unseen data domain. However, existing solutions often neglect either crossing cameras (e.g., illumination and resolution differences) or pedestrian misalignments (e.g., viewpoint and pose discrepancies), which easily leads to poor generalization capability when adapted to the new domain. In this paper, we formulate these difficulties as: 1) Camera-Camera (CC) problem, which denotes the various human appearance changes caused by different cameras; 2) Camera-Person (CP) problem, which indicates the pedestrian misalignments caused by the same identity person under different camera viewpoints or changing pose. To solve the above issues, we propose a Bi-stream Generative Model (BGM) to learn the fine-grained representations fused with camera-invariant global feature and pedestrian-aligned local feature, which contains an encoding network and two stream decoding sub-networks. Guided by original pedestrian images, one stream is employed to learn a camera-invariant global feature for the CC problem via filtering cross-camera interference factors. For the CP problem, another stream learns a pedestrian-aligned local feature for pedestrian alignment using information-complete densely semantically aligned part maps. Moreover, a part-weighted loss function is presented to reduce the influence of missing parts on pedestrian alignment. Extensive experiments demonstrate that our method outperforms the state-of-the-art methods on the large-scale generalizable re-ID benchmarks, involving domain generalization setting and cross-domain setting.

cs.CV↗

arXiv2022

Weakly-supervised 3D Human Pose Estimation with Cross-view U-shaped Graph Convolutional Network

Although monocular 3D human pose estimation methods have made significant progress, it is far from being solved due to the inherent depth ambiguity. Instead, exploiting multi-view information is a practical way to achieve absolute 3D human pose estimation. In this paper, we propose a simple yet effective pipeline for weakly-supervised cross-view 3D human pose estimation. By only using two camera views, our method can achieve state-of-the-art performance in a weakly-supervised manner, requiring no 3D ground truth but only 2D annotations. Specifically, our method contains two steps: triangulation and refinement. First, given the 2D keypoints that can be obtained through any classic 2D detection methods, triangulation is performed across two views to lift the 2D keypoints into coarse 3D poses. Then, a novel cross-view U-shaped graph convolutional network (CV-UGCN), which can explore the spatial configurations and cross-view correlations, is designed to refine the coarse 3D poses. In particular, the refinement progress is achieved through weakly-supervised learning, in which geometric and structure-aware consistency checks are performed. We evaluate our method on the standard benchmark dataset, Human3.6M. The Mean Per Joint Position Error on the benchmark dataset is 27.4 mm, which outperforms existing state-of-the-art methods remarkably (27.4 mm vs 30.2 mm).

cs.CV↗

arXiv2022

Spurious currents suppression by accurate difference schemes in multiphase lattice Boltzmann method

Spurious currents, which are often observed near a curved interface in the multiphase simulations by diffuse interface methods, are unphysical phenomena and usually damage the computational accuracy and stability. In this paper, the origination and suppression of spurious currents are investigated by using the multiphase lattice Boltzmann method driven by chemical potential. Both the difference error and insufficient isotropy of discrete gradient operator give rise to the directional deviations of nonideal force and then originate the spurious currents. Nevertheless, the high-order finite difference produces far more accurate results than the high-order isotropic difference. We compare several finite difference schemes which have different formal accuracy and resolution. When a large proportional coefficient is used, the transition region is narrow and steep, and the resolution of finite difference indicates the computational accuracy more exactly than the formal accuracy. On the contrary, for a small proportional coefficient, the transition region is wide and gentle, and the formal accuracy of finite difference indicates the computational accuracy better than the resolution. Furthermore, numerical simulations show that the spurious currents calculated in the 3D situation are highly consistent with those in 2D simulations; especially, the two-phase coexistence densities calculated by the high-order accuracy finite difference are in excellent agreement with the theoretical predictions of the Maxwell equal-area construction till the reduced temperature 0.2.

physics.comp-ph↗

arXiv2022

Noncontact measurement method of linear and angular displacement based on dual-beam feedback interferometric system

This study describes a unique optical approach for the noncontact measurement of linear and angular displacement. Compared to previous methods, the sensor system here based on the dual-beam phase-modulated feedback interferometry provides higher sensitivity for non-cooperative targets and a wider range concerning the angle measurement. The amount of linear and angular displacement is calculated by tracing the phase changes of the differential beams. Performance of the proposed method is evaluated via testing a prototype system. The prototype has a 35 nm and 0.15" stability over 1 hour, with a resolution of 1 nm and 0.02" correspondingly, according to the experimental data. The linearity is 5.58*10^{-6} in the range of 100 mm and 1.34*10^{-4} in the range of 360°, indicating that the proposed method may possess considerable potential for high-precision metrological applications.

physics.optics↗

arXiv2022

Robust Tube-based Model Predictive Control with Koopman Operators--Extended Version

Koopman operators are of infinite dimension and capture the characteristics of nonlinear dynamics in a lifted global linear manner. The finite data-driven approximation of Koopman operators results in a class of linear predictors, useful for formulating linear model predictive control (MPC) of nonlinear dynamical systems with reduced computational complexity. However, the robustness of the closed-loop Koopman MPC under modeling approximation errors and possible exogenous disturbances is still a crucial issue to be resolved. Aiming at the above problem, this paper presents a robust tube-based MPC solution with Koopman operators, i.e., r-KMPC, for nonlinear discrete-time dynamical systems with additive disturbances. The proposed controller is composed of a nominal MPC using a lifted Koopman model and an off-line nonlinear feedback policy. The proposed approach does not assume the convergence of the approximated Koopman operator, which allows using a Koopman model with a limited order for controller design. Fundamental properties, e.g., stabilizability, observability, of the Koopman model are derived under standard assumptions with which, the closed-loop robustness and nominal point-wise convergence are proven. Simulated examples are illustrated to verify the effectiveness of the proposed approach.

eess.SY↗