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Researcher profile

Abid Ali

Abid Ali contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Artificial Intelligencecond-mat.mtrl-scicond-mat.quant-gaseess.SYmath.GRmath.NTmath.QAmath.RTNetworking and Internet Architecturephysics.chem-phquant-phSystems and Control

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Published work

7 published item(s)

preprint2026arXiv

3D UAV Trajectory Design for Fair and Energy-Efficient Communication: A Deep Reinforcement Learning Technique

In different situations, like disaster communication and network connectivity for rural locations, unmanned aerial vehicles (UAVs) could indeed be utilized as airborne base stations to improve both the functionality and coverage of communication networks. Ground users can employ mobile UAVs to establish communication channels and deliver packages. UAVs, on the other hand, have restricted transmission capabilities and fuel supplies. They can't always cover the full region or continue to fly for a long time, especially in a huge territory. Controlling a swarm of UAVs to yield a relatively long communication coverage while maintaining connectivity and limiting energy usage is so difficult. We use modern deep reinforcement learning (DRL) for UAV connectivity to provide an innovative and extremely energy-efficient DRL-based algorithm. The proposed method: 1) enhances novel energy efficiency while taking into account communications throughput, energy consumption, fairness, and connectivity; 2) evaluates the environment and its dynamics; and 3) makes judgments using strong deep neural networks. For performance evaluation, we have performed comprehensive simulations. In terms of energy consumption and fairness, simulation results show that the DRL-based algorithm consistently outperforms two commonly used baseline techniques.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Measuring What Matters Beyond Text: Evaluating Multimodal Summaries by Quality, Alignment, and Diversity

Multimodal Large Language Models (MLLMs) have facilitated Multimodal Summarization with Multimodal Output (MSMO), wherein systems generate concise textual summaries accompanied by salient visuals from multimodal sources. However, current MSMO evaluation remains fragmented: text quality, image-text alignment, and visual diversity are typically assessed in isolation using unimodal metrics, making it difficult to capture whether the modalities jointly support a faithful and useful summary. To address this gap, we introduce MM-Eval, a unified evaluation framework that integrates assessments of textual quality, cross-modal alignment, and visual diversity. MM-Eval comprises three components: (1) text quality, measured using OpenFActScore for factual consistency and G-Eval for coherence, fluency, and relevance; (2) image-text relevance, evaluated via an MLLM-as-a-judge approach; and (3) image-set diversity, quantified using Truncated CLIP Entropy. We calibrate MM-Eval through a learned aggregation model trained on the mLLM-EVAL news benchmark, aligning component contributions with human preferences. Our analysis reveals a text-dominant hierarchy in this setting, where factual consistency acts as a critical determinant of perceived overall quality, while visual relevance and diversity provide complementary signals. MM-Eval improves over heuristic aggregation baselines and provides an interpretable, reference-weak framework for comparative evaluation of multimodal summaries.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Prosummability in Kac--Moody groups

Let $\mathfrak{g}$ be a symmetrizable Kac--Moody algebra. We describe {standard graded} $\mathfrak{g}$-modules $V$, which we use to construct a completion $\widehat{V}$ and pro-unipotent group $\widehat{U}$ in $\GL(\widehat{V})$. These standard graded modules include the adjoint module, all integrable modules, Category~$\mathcal{O}$ modules, and opposite Category~$\mathcal{O}$ modules. We prove that the elements of $\widehat{U}$ are pro-summable series, that is, they are projective limits of summable series on quotients $\widehat{V}/\prod_{j=k}^\infty{V}_j$, for each $k>0$. We give an explicit construction of root subalgebras and their completions, corresponding to every root including the imaginary roots. We also construct complete root groups for imaginary roots, whose elements are also pro-summable series acting on $\widehat{V}$. We show that these groups are isomorphic to groups of power series in variables corresponding to basis elements for the imaginary root space.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Towards Visually Grounded Multimodal Summarization via Cross-Modal Transformer and Gated Attention

Multimodal summarization requires models to jointly understand textual and visual inputs to generate concise, semantically coherent summaries. Existing methods often inject shallow visual features into deep language models, leading to representational mismatches and weak cross-modal grounding. We propose a unified framework that jointly performs text summarization and representative image selection. Our system, SPeCTrA-Sum (Sampler Perceiver with Cross-modal Transformer and gated Attention for Summarization), introduces two key innovations. First, a Deep Visual Processor (DVP) aligns the visual encoder with the language model at corresponding depths, enabling hierarchical, layer-wise fusion that preserves semantic consistency. Second, a lightweight Visual Relevance Predictor (VRP) selects salient and diverse images by distilling soft labels from a Determinantal Point Processes (DPP) teacher. SPeCTrA-Sum is trained using a multi-objective loss that combines autoregressive summarization, cross-modal alignment, and DPP-based distillation. Experiments show that our system produces more accurate, visually grounded summaries and selects more representative images, demonstrating the benefits of depth-aware fusion and principled image selection for multimodal summarization.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Eisenstein series on arithmetic quotients of rank 2 Kac--Moody groups over finite fields

Let $G$ be an affine or hyperbolic rank 2 Kac--Moody group over a finite field $\mathbb F_q$. Let $X=X_{q+1}$ be the Tits building of $G$, the $(q+1)$--homogeneous tree, and let $Γ$ be a non-uniform lattice in $G$. When $Γ$ is a standard parabolic subgroup for the negative $BN$--pair, we define Eisenstein series on $Γ\backslash X$ and prove its convergence in a half space using Iwasawa decomposition of the Haar measure on $G$. A crucial tool is a description of the vertices of $X$ in terms of Iwasawa cells. We also prove meromorphic continuation of the Eisenstein series. This requires us to construct an integral operator on the Tits building $X$ and a truncation operator for the Eisenstein series. We also develop the functional analytic framework necessary for proving meromorphic continuation in our setting, by refining and extending Bernstein's Continuation Principle.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Indirect Mechanism of Au adatom Diffusion on the Si(100) Surface

Calculations of the diffusion of a Au adatom on the dimer reconstructed Si(100)-2x1 surface reveal an interesting mechanism that differs significantly from a direct path between optimal binding sites, which are located in between dimer rows. Instead, the active diffusion mechanism involves promotion of the adatom to higher energy sites on top of a dimer row and then fast migration along the row, visiting ca. a hundred sites at room temperature, before falling back down into an optimal binding site. This top-of-row mechanism becomes more important the lower the temperature is. The calculations are carried out by finding minimum energy paths on the energy surface obtained from density functional theory within the PBEsol functional approximation followed by kinetic Monte Carlo simulations of the diffusion over a range of temperature from 200 K to 900 K. While the activation energy for the direct diffusion mechanism is calculated to be 0.84 eV, the effective activation energy for the indirect mechanism is on average 0.56 eV.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Phase separation and multistability of two-component Bose-Einstein condensate in an optical cavity

We examine the multistability associated with miscibility-immiscibility conditions for a two-component Bose-Einstein condensate coupled to the light field in an optical cavity. For a strongly immiscible condition, the system exhibits a variety of density structures, including separated state, stripe state, and their coexistence. The multistability arises from these spatial structures of the two-component condensate, which significantly alter the hysteresis curve with respect to the intensity of cavity pumping. We present a variational approach to confirm our numerical results.

0 citations0 reviewsNo code linkedOpen access