arXiv subjects

Shi Wang

Publications and source records attributed to Shi Wang.

At least 55 records · Page 3Linked to original sources

arXiv2022

HieNet: Bidirectional Hierarchy Framework for Automated ICD Coding

International Classification of Diseases (ICD) is a set of classification codes for medical records. Automated ICD coding, which assigns unique International Classification of Diseases codes with each medical record, is widely used recently for its efficiency and error-prone avoidance. However, there are challenges that remain such as heterogeneity, label unbalance, and complex relationships between ICD codes. In this work, we proposed a novel Bidirectional Hierarchy Framework(HieNet) to address the challenges. Specifically, a personalized PageRank routine is developed to capture the co-relation of codes, a bidirectional hierarchy passage encoder to capture the codes' hierarchical representations, and a progressive predicting method is then proposed to narrow down the semantic searching space of prediction. We validate our method on two widely used datasets. Experimental results on two authoritative public datasets demonstrate that our proposed method boosts state-of-the-art performance by a large margin.

cs.AI↗

arXiv2022

CKG: Dynamic Representation Based on Context and Knowledge Graph

Recently, neural language representation models pre-trained on large corpus can capture rich co-occurrence information and be fine-tuned in downstream tasks to improve the performance. As a result, they have achieved state-of-the-art results in a large range of language tasks. However, there exists other valuable semantic information such as similar, opposite, or other possible meanings in external knowledge graphs (KGs). We argue that entities in KGs could be used to enhance the correct semantic meaning of language sentences. In this paper, we propose a new method CKG: Dynamic Representation Based on \textbf{C}ontext and \textbf{K}nowledge \textbf{G}raph. On the one side, CKG can extract rich semantic information of large corpus. On the other side, it can make full use of inside information such as co-occurrence in large corpus and outside information such as similar entities in KGs. We conduct extensive experiments on a wide range of tasks, including QQP, MRPC, SST-5, SQuAD, CoNLL 2003, and SNLI. The experiment results show that CKG achieves SOTA 89.2 on SQuAD compared with SAN (84.4), ELMo (85.8), and BERT$_{Base}$ (88.5).

cs.CL↗

arXiv2022

Moto: Enhancing Embedding with Multiple Joint Factors for Chinese Text Classification

Recently, language representation techniques have achieved great performances in text classification. However, most existing representation models are specifically designed for English materials, which may fail in Chinese because of the huge difference between these two languages. Actually, few existing methods for Chinese text classification process texts at a single level. However, as a special kind of hieroglyphics, radicals of Chinese characters are good semantic carriers. In addition, Pinyin codes carry the semantic of tones, and Wubi reflects the stroke structure information, \textit{etc}. Unfortunately, previous researches neglected to find an effective way to distill the useful parts of these four factors and to fuse them. In our works, we propose a novel model called Moto: Enhancing Embedding with \textbf{M}ultiple J\textbf{o}int Fac\textbf{to}rs. Specifically, we design an attention mechanism to distill the useful parts by fusing the four-level information above more effectively. We conduct extensive experiments on four popular tasks. The empirical results show that our Moto achieves SOTA 0.8316 ($F_1$-score, 2.11\% improvement) on Chinese news titles, 96.38 (1.24\% improvement) on Fudan Corpus and 0.9633 (3.26\% improvement) on THUCNews.

cs.CL↗

arXiv2022

Homological norms on nonpositively curved manifolds

We relate the Gromov norm on homology classes to the harmonic norm on the dual cohomology and obtain double sided bounds in terms of the volume and other geometric quantities of the underlying manifold. Along the way, we provide comparisons to other related norms and quantities as well.

math.GT↗

arXiv2022

An $\ell_1$-norm-mass inequality for complete manifolds

We generalize an inequality of Besson-Courtois-Gallot about volume and simplicial volume of closed manifolds to the $\ell_1$-norm of all the homology classes of complete manifolds. The inequality involves the critical exponent of the fundamental group of the manifold and the mass of the homology classes.

math.GT↗

arXiv2022

HERB: Measuring Hierarchical Regional Bias in Pre-trained Language Models

Fairness has become a trending topic in natural language processing (NLP), which addresses biases targeting certain social groups such as genders and religions. However, regional bias in language models (LMs), a long-standing global discrimination problem, still remains unexplored. This paper bridges the gap by analysing the regional bias learned by the pre-trained language models that are broadly used in NLP tasks. In addition to verifying the existence of regional bias in LMs, we find that the biases on regional groups can be strongly influenced by the geographical clustering of the groups. We accordingly propose a HiErarchical Regional Bias evaluation method (HERB) utilising the information from the sub-region clusters to quantify the bias in pre-trained LMs. Experiments show that our hierarchical metric can effectively evaluate the regional bias with respect to comprehensive topics and measure the potential regional bias that can be propagated to downstream tasks. Our codes are available at https://github.com/Bernard-Yang/HERB.

cs.CL↗

arXiv2022

BQA: A High-performance Quantum Circuits Scheduling Strategy Based on Heuristic Search

Currently, quantum computing is developing at a high speed because its high parallelism and high computing power bring new solutions to many fields. However, due to chip process technology, it is difficult to achieve full coupling of all qubits on a quantum chip, so when compiling a quantum circuit onto a physical chip, it is necessary to ensure that the two-qubit gate acts on a pair of coupled qubits by inserting swap gates. It will cause great additional cost when a large number of swap gates are inserted, leading to the execution time of quantum circuits longer. In this paper, we designed a way based on the business to insert swap gates BQA(Busy Qubits Avoid). We exploit the imbalance of the number of gates on qubits, trying to hide the overhead of swap gates. At the same time, we also expect swap gates to make as little negative impact on subsequent two-qubit gates as possible. We have designed a heuristic function that can take into account both of these points. Compared with qiskit, the execution time of the circuit optimized by our proposed method is only 0.5 times that of the qiskit compiled circuit. And when the number of two-qubit gates is large, it will achieve higher level than general conditions. This implies higher execution efficiency and lower decoherence error rate.

quant-ph↗

arXiv2022

Marked length spectrum rigidity for relatively hyperbolic groups

We consider a coarse version of the marked length spectrum rigidity: given a group with two left invariant metrics, if the marked length spectrum (the translation length function) under the two metrics are the same, then the two metrics are uniformly close. We prove the rigidity theorem for relatively hyperbolic groups. This generalizes a result of Fujiwara.

math.GT↗

arXiv2022

Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization

In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages. Given English gold summaries and documents, sentence-level labels for extractive summarization are usually generated using heuristics. However, these monolingual labels created on English datasets may not be optimal on datasets of other languages, for that there is the syntactic or semantic discrepancy between different languages. In this way, it is possible to translate the English dataset to other languages and obtain different sets of labels again using heuristics. To fully leverage the information of these different sets of labels, we propose NLSSum (Neural Label Search for Summarization), which jointly learns hierarchical weights for these different sets of labels together with our summarization model. We conduct multilingual zero-shot summarization experiments on MLSUM and WikiLingua datasets, and we achieve state-of-the-art results using both human and automatic evaluations across these two datasets.

cs.CL↗

arXiv2022

Discrete subgroups of small critical exponent

We prove that finitely generated higher dimensional Kleinian groups with small critical exponent are always convex-cocompact. Along the way, we also prove some geometric properties for any complete pinched negatively curved manifold with critical exponent less than 1.

math.DG↗

arXiv2022

Geometric cycles and bounded cohomology for a cocompact lattice in $SL_n(\mathbb R)$

We show there exists a closed locally symmetric manifold $M$ modeled on $SL_n(\mathbb R)/SO(n)$, and a non-trivial homology class in degree $dim(M)-rank(M)$ represented by a totally geodesic submanifold that contains a circle factor. As a result, the comparison map $c^k:H_b^k(M,\mathbb R)\rightarrow H^k(M,\mathbb R)$ is not surjective in degree $k=dim(M)-rank(M)$. This provides a counterpart to a result of Lafont-Wang which states that $c^k$ is always surjective in degree $k\geq dim(M)-rank(M)+2$.

math.GT↗

arXiv2022

Photonics-Assisted Joint Communication-Radar System Based on a QPSK-Sliced Linearly Frequency-Modulated Signal

A photonics-assisted joint communication-radar system is proposed and experimentally demonstrated, by introducing a quadrature phase-shift keying (QPSK)-sliced linearly frequency-modulated (LFM) signal. An LFM signal is carrier-suppressed single-sideband modulated onto the optical carrier in one dual-parallel Mach-Zehnder modulator (DPMZM) of a dual-polarization dual-parallel Mach-Zehnder modulator (DPol-DPMZM). The other DPMZM of the DPol-DPMZM is biased as an IQ modulator to implement QPSK modulation on the optical carrier. The polarization orthogonal optical signals from the DPol-DPMZM are further combined and detected in a photodetector to generate the QPSK-sliced LFM signal, which is used to realize efficient data transmission and high-performance radar functions including ranging and imaging. An experiment is carried out. Radar range detection with an error of less than 4 cm, ISAR imaging with a resolution of 14.99 cm*3.25 cm, and communication with a data rate of 105.26 Mbit/s are successfully verified.

eess.SP↗

arXiv2021

Cheeger-Gromoll Splitting Theorem for groups

We study a notion of curvature for finitely generated groups which serves as a role of Ricci curvature for Riemannian manifolds. We prove an analog of Cheeger-Gromoll splitting theorem. As a consequence, we give a geometric characterization of virtually abelian groups. We also explore the relation between this notion of curvature and the growth of groups.

math.GR↗

arXiv2021

A review of Quantum Neural Networks: Methods, Models, Dilemma

The rapid development of quantum computer hardware has laid the hardware foundation for the realization of QNN. Due to quantum properties, QNN shows higher storage capacity and computational efficiency compared to its classical counterparts. This article will review the development of QNN in the past six years from three parts: implementation methods, quantum circuit models, and difficulties faced. Among them, the first part, the implementation method, mainly refers to some underlying algorithms and theoretical frameworks for constructing QNN models, such as VQA. The second part introduces several quantum circuit models of QNN, including QBM, QCVNN and so on. The third part describes some of the main difficult problems currently encountered. In short, this field is still in the exploratory stage, full of magic and practical significance.

cs.ET↗

arXiv2020

Comprehensive study of the global phase diagram in the triangular $J$-$K$-$Γ$ model

The celebrated Kitaev honeycomb model provides an analytically tractable example with an exact quantum spin liquid ground state. While in real materials, other types of interactions besides the Kitaev coupling ($K$) are present, such as the Heisenberg ($J$) and symmetric off-diagonal ($Γ$) terms, and these interactions can also be generalized to a triangular lattice. Here, we carry out a comprehensive study of the $J$-$K$-$Γ$ model on the triangular lattice covering the full parameters region, using the combination of the exact diagonalization, classical Monte Carlo and analytic methods. In the HK limit ($Γ=0$), we find five quantum phases which are quite similar to their classical counterparts. Among them, the stripe-A and dual Néel phase are robust against the $Γ$ term, in particular the stripe-A extends to the region connecting the $K=-1$ and $K=1$ for $Γ<0$. Though the 120$^\circ$ Néel phase also extends to a finite $Γ$, its region has been largely reduced compared to the previous classical result. Interestingly, the ferromagnetic (dubbed as FM-A) phase and the stripe-B phase are unstable in response to an infinitesimal $Γ$ interaction. Moreover, we find five new phases for $Γ\ne 0$ which are elaborated by both the quantum and classical numerical methods. Part of the space previously identified as 120$^\circ$ Néel phase in the classical study is found to give way to the modulated stripe phase. Depending on the sign of the $Γ$, the FM-A phase transits into the FM-B ($Γ>0$) and FM-C ($Γ<0$) phase with different spin orientations, and the stripe-B phase transits into the stripe-C ($Γ>0$) and stripe-A ($Γ<0$). Around the positive $Γ$ point, due to the interplay of the Heisenberg, Kiatev and $Γ$ interactions, we find a possible quantum spin liquid with a continuum in spin excitations.

cond-mat.str-el↗

arXiv2020

HIN: Hierarchical Inference Network for Document-Level Relation Extraction

Document-level RE requires reading, inferring and aggregating over multiple sentences. From our point of view, it is necessary for document-level RE to take advantage of multi-granularity inference information: entity level, sentence level and document level. Thus, how to obtain and aggregate the inference information with different granularity is challenging for document-level RE, which has not been considered by previous work. In this paper, we propose a Hierarchical Inference Network (HIN) to make full use of the abundant information from entity level, sentence level and document level. Translation constraint and bilinear transformation are applied to target entity pair in multiple subspaces to get entity-level inference information. Next, we model the inference between entity-level information and sentence representation to achieve sentence-level inference information. Finally, a hierarchical aggregation approach is adopted to obtain the document-level inference information. In this way, our model can effectively aggregate inference information from these three different granularities. Experimental results show that our method achieves state-of-the-art performance on the large-scale DocRED dataset. We also demonstrate that using BERT representations can further substantially boost the performance.

cs.CL↗

arXiv2020

Negative compressibility in MoS2 capacitance

Large capacitance enhancement is useful for increasing the gate capacitance of field-effect transistors (FETs) to produce low-energy-consuming devices with improved gate controllability. We report strong capacitance enhancement effects in a newly emerged two-dimensional channel material, molybdenum disulfide (MoS2). The enhancement effects are due to strong electron-electron interaction at the low carrier density regime in MoS2. We achieve about 50% capacitance enhancement in monolayer devices and 10% capacitance enhancement in bilayer devices. However, the enhancement effect is not obvious in multilayer (layer number >3) devices. Using the Hartree-Fock approximation, we illustrate the same trend in our inverse compressibility data.

physics.app-ph↗

arXiv2019

Realization of metallic state in 1T-TaS2 with persisting long-range order of charge density wave

Metallization of 1T-TaS2 is generally initiated at the domain boundary of charge density wave (CDW), at the expense of its long-range order. However, we demonstrate in this study that the metallization of 1T-TaS2 can be also realized without breaking the long-range CDW order upon surface alkali doping. By using scanning tunneling microscopy, we find the long-range CDW order is always persisting, and the metallization is instead associated with additional in-gap excitations. Interestingly, the in-gap excitation is near the top of the lower Hubbard band, in contrast to a conventional electron-doped Mott insulator where it is beneath the upper Hubbard band. In combination with the numerical calculations, we suggest that the appearance of the in-gap excitations near the lower Hubbard band is mainly due to the effectively reduced on-site Coulomb energy by the adsorbed alkali ions.

cond-mat.str-el↗