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arXiv:2310.00488v4 Announce Type: replace Abstract: Optimization algorithms that seek flatter minima, such as Sharpness-Aware Minimization (SAM), are credited with improved generalization and robustness to noise....
arXiv:2310.03606v2 Announce Type: replace Abstract: This literature review aimed to compare various time-series analysis approaches utilized in forecasting COVID-19 cases in Africa. The study involved...
arXiv:2311.12086v3 Announce Type: replace Abstract: Neural Architecture Search (NAS) relies heavily on labeled data, which is labor-intensive and time-consuming to obtain. In this paper, we...
arXiv:2401.06157v2 Announce Type: replace Abstract: Invasive signal crayfish have a detrimental impact on ecosystems. They spread the fungal-type crayfish plague disease (Aphanomyces astaci) that is...
arXiv:2402.01666v2 Announce Type: replace Abstract: With the development of artificial intelligence, personalized learning has attracted much attention as an integral part of intelligent education. In...
arXiv:2402.03578v3 Announce Type: replace Abstract: This paper explores multi-agent systems and identify challenges that remain inadequately addressed. By leveraging the diverse capabilities and roles of...
arXiv:2402.15769v3 Announce Type: replace Abstract: Pre-trained code models lead the era of code intelligence, with multiple models designed with impressive performance. However, one important problem,...
arXiv:2404.09256v2 Announce Type: replace Abstract: Foundation models trained with self-supervised objectives are increasingly applied to brain recordings, but autoregressive generation of realistic multichannel neural time...
arXiv:2404.13879v4 Announce Type: replace Abstract: Uncertainties in transition dynamics pose a critical challenge in reinforcement learning (RL), often resulting in performance degradation of trained policies...
arXiv:2405.07060v2 Announce Type: replace Abstract: Visual Language Navigation (VLN) powered robots have the potential to guide blind people by understanding route instructions provided by sighted...
arXiv:2406.08844v2 Announce Type: replace Abstract: While multi-agent reinforcement learning (MARL) has produced numerous algorithms that converge to Nash or related equilibria, such equilibria are often...
arXiv:2407.10853v4 Announce Type: replace Abstract: Bias and fairness risks in Large Language Models (LLMs) vary substantially across deployment contexts, yet existing approaches lack systematic guidance...
arXiv:2408.04628v2 Announce Type: replace Abstract: Standard natural language processing (NLP) pipelines operate on symbolic representations of language, which typically consist of sequences of discrete tokens....
arXiv:2408.11345v5 Announce Type: replace Abstract: Although advancements in deep learning have significantly enhanced the recommendation accuracy of deep recommendation models, these methods still suffer from...
arXiv:2408.11987v2 Announce Type: replace Abstract: We introduce SimBench, a benchmark designed to evaluate the proficiency of simulator-oriented LLMs (S-LLMs) in generating digital twins (DTs) that...
arXiv:2409.12023v3 Announce Type: replace Abstract: In this work, we study the numerical approximation of minimizers of the Ginzburg-Landau free energy, a common model to describe...
arXiv:2410.01262v5 Announce Type: replace Abstract: While many diffusion models perform well when controlling particular aspects such as style, character, and interaction, they struggle with fine-grained...
arXiv:2410.03573v3 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful approach for solving partial differential equations (PDEs) by training neural networks...
arXiv:2410.08314v5 Announce Type: replace Abstract: In this paper we study the Spanning Tree Congestion problem, where we are given a graph $G=(V,E)$ and are asked...
arXiv:2410.09562v2 Announce Type: replace Abstract: Situational visual impairments (SVIs) hinder mobile readability, causing discomfort and limiting information access. Building on prior work in adaptive typography...
arXiv:2411.02576v2 Announce Type: replace Abstract: Decision-makers consult multiple forecasts to account for uncertainties when forming judgments about future events. While prior works have compared unaggregated...
arXiv:2411.08127v4 Announce Type: replace Abstract: TIPO (Text-to-Image Prompt Optimization) introduces an efficient approach for automatic prompt refinement in text-to-image (T2I) generation. Starting from simple user...
arXiv:2411.08862v2 Announce Type: replace Abstract: We introduce LLMStinger, a novel approach that leverages Large Language Models (LLMs) to automatically generate adversarial suffixes for jailbreak attacks....
arXiv:2411.15955v4 Announce Type: replace Abstract: Inter-symbol interference (ISI) limits reliability in diffusion-based molecular communication (MC) channels. We propose RLIM, a family of run-length-limited (RLL) codes...