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Multi-modal Large Language Models (MLLMs) have exhibited impressive capability. However, recently many deficiencies of MLLMs have been found compared to human intelligence, $\textit{e.g.}$, hallucination. To drive the MLLMs study, the community dedicated efforts to building larger benchmarks with complex tasks. In this paper, we propose benchmarking an essential but usually overlooked intelligence: $\textbf{association}$, a human's basic capability to link observation and prior practice memory. To comprehensively investigate MLLM's performance on the association, we formulate the association task and devise a standard benchmark based on adjective and verb semantic concepts. Instead of costly data annotation and curation, we propose a convenient $\textbf{annotation-free}$ construction method transforming the general dataset for our association tasks. Simultaneously, we devise a rigorous data refinement process to eliminate confusion in the raw dataset. Building on this database, we establish three levels of association tasks: single-step, synchronous, and asynchronous associations. Moreover, we conduct a comprehensive investigation into the MLLMs' zero-shot association capabilities, addressing multiple dimensions, including three distinct memory strategies, both open-source and closed-source MLLMs, cutting-edge Mixture-of-Experts (MoE) models, and the involvement of human experts. Our systematic investigation shows that current open-source MLLMs consistently exhibit poor capability in our association tasks, even the currently state-of-the-art GPT-4V(vision) also has a significant gap compared to humans. We believe our benchmark would pave the way for future MLLM studies. $\textit{Our data and code are available at:}$ https://mvig-rhos.com/llm_inception.

Reading ability detection is important in modern educational field. In this paper, a method of predicting scores of reading ability is proposed, using the eye-tracking data of a few subjects (e.g., 68 subjects). The proposed method built a regression model for the score prediction by combining Long Short Time Memory (LSTM) and light-weighted neural networks. Experiments show that with few-shot learning strategy, the proposed method achieved higher accuracy than previous methods of score prediction in reading ability detection. The code can later be downloaded at https://github.com/pumpkinLNX/LSTM-eye-tracking-pytorch.git

A novel multicast communication system with movable antennas (MAs) is proposed, where the antenna position optimization is exploited to enhance the transmission rate. Specifically, an MA-assisted two-user multicast multiple-input single-input system is considered. The joint optimization of the transmit beamforming vector and transmit MA positions is studied by modeling the motion of the MA elements as discrete movements. A low-complexity greedy search-based algorithm is proposed to tackle this non-convex inter-programming problem. A branch-and-bound (BAB)-based method is proposed to achieve the optimal multicast rate with a reduced time complexity than the brute-force search by assuming the two users suffer similar line-of-sight path losses. Numerical results reveal that the proposed MA systems significantly improve the multicast rate compared to conventional fixed-position antennas (FPAs)-based systems., Comment: 5 pages

Scandium aluminum nitride (ScAlN) has recently emerged as an attractive material for integrated photonics due to its favorable nonlinear optical properties and compatibility with CMOS fabrication. Despite the promising and versatile material properties, it is still an outstanding challenge to realize low-loss photonic circuits on thin-film ScAlN-on-insulator wafers. Here, we present a systematic study on the material quality of sputtered thin-film ScAlN produced in a CMOS-compatible 200 mm line, and an optimized fabrication process to yield 400 nm thick, fully etched waveguides. With surface polishing and annealing, we achieve micro-ring resonators with an intrinsic quality factor as high as $1.47\times 10^5$, corresponding to a propagation loss of 2.4 dB/cm. These results serve as a critical step towards developing future large-scale, low-loss photonic integrated circuits based on ScAlN.

We develop a theoretical predictive model for an all-pass ring resonator that enables the most complete description of linear coupling regimes. The model is based on eigenmode decomposition of Maxwell's equations with full account of the confined and leaky modes, as opposed to the existing phenomenological methods restricted to the confined modes only. This model enables quantitative description of all-pass ring resonators and provides insights into the physics underlying microring-waveguide coupling. We experimentally validate the model using transmission measurements in the linear regime of aluminium nitride resonators. The developed model is then used to explore the field enhancement in microrings crucial for nonlinear photonic applications., Comment: 8 pages, 11 figures

A pioneering secure transmission scheme is proposed, which harnesses movable antennas (MAs) to optimize antenna positions for augmenting the physical layer security. Particularly, an MA-enabled secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. The beamformer and antenna positions at the transmitter are jointly optimized under two criteria: power consumption minimization and secrecy rate maximization. For each scenario, a novel suboptimal algorithm was proposed to tackle the resulting nonconvex optimization problem, capitalizing on the approaches of alternating optimization and gradient descent. Numerical results demonstrate that the proposed MA systems significantly improve physical layer security compared to various benchmark schemes relying on conventional fixed-position antennas (FPAs)., Comment: Accepted by IEEE ICASSP 2024

Active reconfigurable intelligent surface (ARIS) is a newly emerging RIS technique that leverages radio frequency (RF) reflection amplifiers to empower phase-configurable reflection elements (REs) in amplifying the incident signal. Thereby, ARIS can enhance wireless communications with the strengthened ARIS-aided links. In this letter, we propose exploiting the signal amplification capability of ARIS for channel estimation, aiming to improve the estimation precision. Nevertheless, the signal amplification inevitably introduces the thermal noise at the ARIS, which can hinder the acquisition of accurate channel state information (CSI) with conventional channel estimation methods based on passive RIS (PRIS). To address this issue, we further investigate this ARIS-specific channel estimation problem and propose a least-square (LS) based channel estimator, whose performance can be further improved with the design on ARIS reflection patterns at the channel training phase. Based on the proposed LS channel estimator, we optimize the training reflection patterns to minimize the channel estimation error variance. Extensive simulation results show that our proposed design can achieve accurate channel estimation in the presence of the ARIS noises., Comment: This paper has been accepted for publication in IEEE Wireless Communications Letters

A novel over-the-air computation (AirComp) framework, empowered by the incorporation of movable antennas (MAs), is proposed to significantly enhance computation accuracy. Within this framework, the joint optimization of transmit power control, antenna positioning, and receive combining is investigated. An efficient method is proposed to tackle the problem of computation mean-squared error (MSE) minimization, capitalizing on the approach of alternating optimization. Numerical results are provided to substantiate the superior MSE performance of the proposed framework, which establish its clear advantage over benchmark systems employing conventional fixed-position antennas (FPAs).

A novel multiuser communication system with movable antennas (MAs) is proposed, where the antenna position optimization is exploited to enhance the downlink sum-rate. The joint optimization of the transmit beamforming vector and transmit MA positions is studied for a multiuser multiple-input single-input system. An efficient algorithm is proposed to tackle the formulated non-convex problem via capitalizing on fractional programming, alternating optimization, and gradient descent methods. To strike a better performance-complexity trade-off, a zero-forcing beamforming-based design is also proposed as an alternative. Numerical investigations are presented to verify the efficiency of the proposed algorithms and their superior performance compared with the benchmark relying on conventional fixed-position antennas (FPAs)., Comment: 11 pages

Capping layers are essential for protecting phase change materials (PCMs) used in non-volatile photonics technologies. This work demonstrates how $(ZnS)_{0.8}-(SiO_2)_{0.2}$ caps radically influence the performance of $Sb_{2}S_{3}$ and Ag-doped $Sb_{2}S_{3}$ integrated photonic devices. We found that at least 30 nm of capping material is necessary to protect the material from Sulfur loss. However, adding this cap affects the crystallization temperatures of the two PCMs in different ways. The crystallization temperature of $Sb_{2}S_{3}$ and Ag-doped $Sb_{2}S_{3}$ increased and decreased respectively, which is attributed to interfacial energy differences. Capped and uncapped Ag-doped $Sb_{2}S_{3}$ microring resonator (MRR) devices were fabricated and measured to understand how the cap affects the device performance. Surprisingly, the resonant frequency of the MRR exhibited a larger red-shift upon crystallization for the capped PCMs. This effect was due to the cap increasing the modal overlap with the PCM layer. Caps can, therefore, be used to provide a greater optical phase shift per unit length, thus reducing the overall footprint of these programmable devices. Overall, we conclude that caps on PCMs are not just useful for stabilizing the PCM layer, but can also be used to tune the PCM crystallization temperature and reduce device footprint. Moreover, the capping layer can be exploited to enhance light-matter interactions with the PCM element.

This work proposes a novel joint design for multiuser multiple-input multiple-output wiretap channels. The base station exploits a switching network to connect a subset of its antennas to the available radio frequency chains. The switching network and transmit beamformers are jointly designed to maximize the weighted secrecy sum-rate for this setting. The principal design problem reduces to an NP-hard mixed-integer non-linear programming. We invoke the fractional programming technique and the penalty dual decomposition method to develop a tractable iterative algorithm that effectively approximates the optimal design. Our numerical investigations validate the effectiveness of the proposed algorithm and its superior performance compared with the benchmark., Comment: 6 pages. arXiv admin note: substantial text overlap with arXiv:2212.13684

Metalenses built up by artificial sub-wavelength nanostructures have shown the capability of realizing light focusing with miniature lens size. To date, most of the reported metalenses were patterned using electron beam lithography (EBL), which requires long processing time and is not suitable for mass production. Here, we demonstrate an amorphous silicon (a-Si) metalens on a 12-inch glass wafer via the 193 nm ArF deep UV immersion lithography, with critical dimension (CD) as small as 100 nm. The layer transfer technology is developed to solve the glass wafer handling issue in complementary metal-oxide-semiconductor (CMOS) fabrication line. The measured numerical aperture (NA) is 0.494 with a beam spot size of 1.26 {\mu}m, which agrees well with the simulation results. The focusing efficiency of 29.2% is observed at the designed wavelength of 940 nm. In addition, the metalens is applied in an imaging system, which further verifies its focusing functionality.

Ability to selectively enhance the amplitude and maintain high coherence of the supercontinuum signal with long pulses is gaining significance. In this work an extra degree of freedom afforded by varying the dispersion profile of a waveguide is utilized to selectively enhance supercontinuum. As much as 16 dB signal enhancement in the telecom window and 100 nm of wavelength extension is achieved with a cascaded waveguide, compared to a fixed dispersion waveguide. Waveguide tapering, in particular with increasing width, is determined to have a flatter and more coherent supercontinuum than a fixed dispersion waveguide when longer input pulses are used. Furthermore, due to the strong birefringence of an asymmetric silicon waveguide the supercontinuum signal is broadened by pumping simultaneously with both quasitransverse electric (TE) and quasi-transverse magnetic (TM) mode in the anomalous dispersion regime. Thus, by controlling the dispersion for the two modes selective signal generation is obtained. Such waveguides offer several advantages over optical fiber as the variation in dispersion can be controlled with greater flexibility in an integrated platform. This work paves the way forward for various applications in fields ranging from medicine to telecom where specific wavelength windows need to be targeted., Comment: 14 pages, 10 figures