Incomplete Utterance Rewriting as Sequential Greedy Tagging

The task of incomplete utterance rewriting has recently gotten much attention. Previous models struggled to extract information from the dialogue context, as evidenced by the low restoration scores. To address this issue, we propose a novel sequence tagging-based model, which is more adept at extracting information from context. Meanwhile, we introduce speaker-aware embedding to model speaker variation. Experiments on multiple public datasets show that our model achieves optimal results on all nine restoration scores while having other metric scores comparable to previous state-of-the-art models. Furthermore, benefitting from the model's simplicity, our approach outperforms most previous models on inference speed.Comment: arXiv admin note: text overlap with arXiv:2009.13166 by other author

Numerical and experimental investigation on self-synchronization of two eccentric rotors in the vibration system

In this paper, we study the coupling dynamic characteristic of a single mass vibration machine driven by two eccentric rotors rotating oppositely. According to the coordinate of rotor flux, we deduce the electromagnetic torque of an induction motor in the steady state operation. From three ways of numerical analysis, model simulation and experiment, we discuss the coupling dynamic characteristic by using the actual parameters of this vibration machine. The results show that when the synchronization condition is satisfied, not only the vibration synchronization transmission can be achieved, but also the synchronization motion of the two motors with different power supply frequencies also can be achieved. The phase of the bigger mass-radius product lags behind that of the smaller one, the phase of the bigger distance between the rotation center of eccentric rotor and the mass center of the vibration rigid body lags behind that of the smaller one, and the phase difference decreases with increasing the synchronization velocity. We present a new method that adjusting the power supply frequencies of the two motors to make the vibration system with different structure parameters carry out the 0 phase difference, and its feasibility is verified by experiment

I&S-ViT: An Inclusive & Stable Method for Pushing the Limit of Post-Training ViTs Quantization

Albeit the scalable performance of vision transformers (ViTs), the dense computational costs (training & inference) undermine their position in industrial applications. Post-training quantization (PTQ), tuning ViTs with a tiny dataset and running in a low-bit format, well addresses the cost issue but unluckily bears more performance drops in lower-bit cases. In this paper, we introduce I&S-ViT, a novel method that regulates the PTQ of ViTs in an inclusive and stable fashion. I&S-ViT first identifies two issues in the PTQ of ViTs: (1) Quantization inefficiency in the prevalent log2 quantizer for post-Softmax activations; (2) Rugged and magnified loss landscape in coarse-grained quantization granularity for post-LayerNorm activations. Then, I&S-ViT addresses these issues by introducing: (1) A novel shift-uniform-log2 quantizer (SULQ) that incorporates a shift mechanism followed by uniform quantization to achieve both an inclusive domain representation and accurate distribution approximation; (2) A three-stage smooth optimization strategy (SOS) that amalgamates the strengths of channel-wise and layer-wise quantization to enable stable learning. Comprehensive evaluations across diverse vision tasks validate I&S-ViT' superiority over existing PTQ of ViTs methods, particularly in low-bit scenarios. For instance, I&S-ViT elevates the performance of 3-bit ViT-B by an impressive 50.68%

Spatial Re-parameterization for N:M Sparsity

This paper presents a Spatial Re-parameterization (SpRe) method for the N:M sparsity in CNNs. SpRe is stemmed from an observation regarding the restricted variety in spatial sparsity present in N:M sparsity compared with unstructured sparsity. Particularly, N:M sparsity exhibits a fixed sparsity rate within the spatial domains due to its distinctive pattern that mandates N non-zero components among M successive weights in the input channel dimension of convolution filters. On the contrary, we observe that unstructured sparsity displays a substantial divergence in sparsity across the spatial domains, which we experimentally verified to be very crucial for its robust performance retention compared with N:M sparsity. Therefore, SpRe employs the spatial-sparsity distribution of unstructured sparsity to assign an extra branch in conjunction with the original N:M branch at training time, which allows the N:M sparse network to sustain a similar distribution of spatial sparsity with unstructured sparsity. During inference, the extra branch can be further re-parameterized into the main N:M branch, without exerting any distortion on the sparse pattern or additional computation costs. SpRe has achieved a commendable feat by matching the performance of N:M sparsity methods with state-of-the-art unstructured sparsity methods across various benchmarks. Code and models are anonymously available at \url{https://github.com/zyxxmu/SpRe}.Comment: 11 pages, 4 figure

Impact of Limited Statistics on the Measured Hyper-Order Cumulants of Net-Proton Distributions in Heavy-Ion Collisions

Hyper-order cumulants $C_5/C_1$ and $C_6/C_2$ of net-baryon distributions are anticipated to offer crucial insights into the phase transition from quark-gluon plasma to hadronic matter in heavy-ion collisions. However, the accuracy of $C_5$ and $C_6$ is highly contingent on the fine shape of the distribution's tail, the detectable range of which could be essentially truncated by low statistics. In this paper, we use the fast Skellam-based simulations, as well as the Ultrarelativistic Quantum Molecular Dynamics model, to assess the impact of limited statistics on the measurements of $C_5/C_1$ and $C_6/C_2$ of net-proton distributions at lower RHIC energies. Both ratios decrease from the unity baseline as we reduce statistics, and could even turn negative without a pertinent physics mechanism. By incorporating statistics akin to experimental data, we can replicate the net-proton $C_5/C_1$ and $C_6/C_2$ values comparable to the corresponding measurements for Au+Au collisions at $\sqrt{s_{NN}} =$ 7.7, 11.5 and 14.5 GeV. Our findings underscore a caveat to the interpretation of the observed beam energy dependence of hyper-order cumulants.Comment: 6 pages, 7 figure

High channel count and high precision channel spacing multi-wavelength laser array for future PICs

Multi-wavelength semiconductor laser arrays (MLAs) have wide applications in wavelength multiplexing division (WDM) networks. In spite of their tremendous potential, adoption of the MLA has been hampered by a number of issues, particularly wavelength precision and fabrication cost. In this paper, we report high channel count MLAs in which the wavelengths of each channel can be determined precisely through low-cost standard μm-level photolithography/holographic lithography and the reconstruction-equivalent-chirp (REC) technique. 60-wavelength MLAs with good wavelength spacing uniformity have been demonstrated experimentally, in which nearly 83% lasers are within a wavelength deviation of ±0.20 nm, corresponding to a tolerance of ±0.032 nm in the period pitch. As a result of employing the equivalent phase shift technique, the single longitudinal mode (SLM) yield is nearly 100%, while the theoretical yield of standard DFB lasers is only around 33.3%

MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization

Arbitrary bit-width network quantization has received significant attention due to its high adaptability to various bit-width requirements during runtime. However, in this paper, we investigate existing methods and observe a significant accumulation of quantization errors caused by frequent bit-width switching of weights and activations, leading to limited performance. To address this issue, we propose MultiQuant, a novel method that utilizes a multi-branch topology for arbitrary bit-width quantization. MultiQuant duplicates the network body into multiple independent branches and quantizes the weights of each branch to a fixed 2-bit while retaining the input activations in the expected bit-width. This approach maintains the computational cost as the same while avoiding the switching of weight bit-widths, thereby substantially reducing errors in weight quantization. Additionally, we introduce an amortization branch selection strategy to distribute quantization errors caused by activation bit-width switching among branches to enhance performance. Finally, we design an in-place distillation strategy that facilitates guidance between branches to further enhance MultiQuant's performance. Extensive experiments demonstrate that MultiQuant achieves significant performance gains compared to existing arbitrary bit-width quantization methods. Code is at \url{https://github.com/zysxmu/MultiQuant}

Synchronization and coupling dynamic characteristics of a dual-rotors exciter

In this work, some theoretical analyses, numerical simulations and experimental results on synchronization of a dual-rotors exciter are given. The exciter is made up of two rotors with eccentric masses (REMs) respectively driven by two DC motors with common axis. By adjusting the phase difference between two REMs to change the response amplitude, the decoupling between response amplitude and exciting frequency can be realized. The motion equations of the vibration system are established by using Lagrange equation, and the dimensionless coupling equations of that are obtained by applying the average method of small parameter. According to the existence condition of the zero solution of the dimensionless coupling equations, the synchronization condition of the vibration system is obtained. The stability condition of the vibration system implementing synchronization motion is acquired based on the principle of Hamilton. Through the comparison between numerical simulations and experimental results, the validity of theoretical analyses is proved, which helps the design of the dual-rotors exciter

Fine-grained Data Distribution Alignment for Post-Training Quantization

While post-training quantization receives popularity mostly due to its evasion in accessing the original complete training dataset, its poor performance also stems from scarce images. To alleviate this limitation, in this paper, we leverage the synthetic data introduced by zero-shot quantization with calibration dataset and propose a fine-grained data distribution alignment (FDDA) method to boost the performance of post-training quantization. The method is based on two important properties of batch normalization statistics (BNS) we observed in deep layers of the trained network, (i.e.), inter-class separation and intra-class incohesion. To preserve this fine-grained distribution information: 1) We calculate the per-class BNS of the calibration dataset as the BNS centers of each class and propose a BNS-centralized loss to force the synthetic data distributions of different classes to be close to their own centers. 2) We add Gaussian noise into the centers to imitate the incohesion and propose a BNS-distorted loss to force the synthetic data distribution of the same class to be close to the distorted centers. By utilizing these two fine-grained losses, our method manifests the state-of-the-art performance on ImageNet, especially when both the first and last layers are quantized to the low-bit. Code is at \url{https://github.com/zysxmu/FDDA}.Comment: ECCV202

Numerical and experimental investigation on self-synchronization of two eccentric rotors in the vibration system

In this paper, we study the coupling dynamic characteristic of a single mass vibration machine driven by two eccentric rotors rotating oppositely. According to the coordinate of rotor flux, we deduce the electromagnetic torque of an induction motor in the steady state operation. From three ways of numerical analysis, model simulation and experiment, we discuss the coupling dynamic characteristic by using the actual parameters of this vibration machine. The results show that when the synchronization condition is satisfied, not only the vibration synchronization transmission can be achieved, but also the synchronization motion of the two motors with different power supply frequencies also can be achieved. The phase of the bigger mass-radius product lags behind that of the smaller one, the phase of the bigger distance between the rotation center of eccentric rotor and the mass center of the vibration rigid body lags behind that of the smaller one, and the phase difference decreases with increasing the synchronization velocity. We present a new method that adjusting the power supply frequencies of the two motors to make the vibration system with different structure parameters carry out the 0 phase difference, and its feasibility is verified by experiment