Stay updated with the latest research and technology news
arXiv:2602.19552v1 Announce Type: new Abstract: In this paper, we consider the problem of replicable realizable PAC learning. We construct a particularly hard learning problem and...
arXiv:2602.19554v1 Announce Type: new Abstract: Orientation and mobility (O&M) instruction for blind and low-vision learners is effective but difficult to standardize and repeat at scale...
arXiv:2602.19555v1 Announce Type: new Abstract: Agentic systems built on large language models (LLMs) extend beyond text generation to autonomously retrieve information and invoke tools. This...
arXiv:2602.19560v1 Announce Type: new Abstract: Ableist language perpetuates harmful stereotypes and exclusion, yet its nuanced nature makes it difficult to recognize and address. Artificial intelligence...
arXiv:2602.19562v1 Announce Type: new Abstract: Establishing stable mappings between natural language expressions and visual percepts is a foundational problem for both cognitive science and artificial...
arXiv:2602.19565v1 Announce Type: new Abstract: Articulated object pose estimation is a core task in embodied AI. Existing methods typically regress poses in a continuous space,...
arXiv:2602.19567v1 Announce Type: new Abstract: Low-diameter topologies such as Dragonfly and Slim Fly are increasingly adopted in HPC and datacenter networks, yet existing load balancing...
arXiv:2602.19569v1 Announce Type: new Abstract: Question Answering over Temporal Knowledge Graphs (TKGQA) has attracted growing interest for handling time-sensitive queries. However, existing methods still struggle...
arXiv:2602.19570v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) can be vulnerable to adversarial images that subtly bias their outputs toward plausible yet incorrect responses....
arXiv:2602.19571v1 Announce Type: new Abstract: Video-LLMs have improved steadily on semantic perception, but they still fall short on predictive world modeling, which is central to...
arXiv:2602.19575v1 Announce Type: new Abstract: Personalized text-to-image generation suffers from concept entanglement, where irrelevant residual information from reference images is captured, leading to a trade-off...
arXiv:2602.19577v1 Announce Type: new Abstract: Autonomous odor source localization remains a challenging problem for aerial robots due to turbulent airflow, sparse and delayed sensory signals,...
arXiv:2602.19580v1 Announce Type: new Abstract: We introduce Leap+Verify, a framework that applies speculative execution -- predicting future model weights and validating predictions before acceptance --...
arXiv:2602.19582v1 Announce Type: new Abstract: Extensive research demonstrates that Deep Reinforcement Learning (DRL) models are susceptible to adversarially constructed inputs (i.e., adversarial examples), which can...
arXiv:2602.19583v1 Announce Type: new Abstract: Comparative evaluation of several systems is a recurrent task in researching. It is a key step before deciding which system...
arXiv:2602.19584v1 Announce Type: new Abstract: Despite the success of machine learning (ML) in surrogate modeling, its use in radiation dose assessment is limited by safety-critical...
arXiv:2602.19585v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) integrates language, visual, and acoustic modalities to infer human sentiment. Most existing methods either focus on...
arXiv:2602.19587v1 Announce Type: new Abstract: Power system operators are increasingly deploying Grid Enhancing Technologies (GETs) to mitigate operational challenges such as line and transformer congestion,...
arXiv:2602.19591v1 Announce Type: new Abstract: Small and Medium Enterprises (SMEs) constitute 99.9% of U.S. businesses and generate 44% of economic activity, yet systematically identifying high-potential...
arXiv:2602.19594v1 Announce Type: new Abstract: We introduce ISO-Bench, a benchmark for coding agents to test their capabilities on real-world inference optimization tasks. These tasks were...
arXiv:2602.19595v1 Announce Type: new Abstract: Generating graphs subject to strict structural constraints is a fundamental computational challenge in network science. Simultaneously preserving interacting properties-such as...
arXiv:2602.19596v1 Announce Type: new Abstract: Collaborative perception (CP) enables data sharing among connected and autonomous vehicles (CAVs) to enhance driving safety. However, CP systems are...
arXiv:2602.19597v1 Announce Type: new Abstract: This paper introduces a Bayesian framework that combines Markov chain Monte Carlo (MCMC) sampling, dimensionality reduction, and neural density estimation...
arXiv:2602.19598v1 Announce Type: new Abstract: Eye-tracking-while-reading corpora are a valuable resource for many different disciplines and use cases. Use cases range from studying the cognitive...