Search: “people”

arXiv:2606.32005v1 Announce Type: cross Abstract: Stochastic Gradient Descent (extsf{SGD}) is one of the most classical optimization algorithms with favorable theoretical guarantees, yet the practical

arXiv:2606.30412v1 Announce Type: cross Abstract: From housing allocation for households experiencing homelessness to triage in emergency departments, LLMs are increasingly being considered as judges

arXiv:2606.29689v1 Announce Type: new Abstract: Open-ended aesthetic critique is a challenge for multimodal large language models (MLLMs): unlike multiple-choice aesthetic benchmarks, it has no single

arXiv:2606.28592v1 Announce Type: new Abstract: Physical caregiving robots need to assist different users with different tasks in diverse environments, and they come in many embodiments. While substan

arXiv:2601.07988v2 Announce Type: replace-cross Abstract: While NLP typically treats documents as independent and unordered samples, in longitudinal studies, this assumption rarely holds: documents ar

arXiv:2606.29808v1 Announce Type: cross Abstract: Chart data extraction, which reverse-engineers data tables from chart images, is essential for reproducibility, analysis, retrieval, and redesign. Exi

arXiv:2606.26502v1 Announce Type: new Abstract: Large reasoning models (LRMs) take longer on harder problems, just as humans do. This surface similarity hides an opposite pattern within items. When an

arXiv:2606.25317v1 Announce Type: new Abstract: An efficient and accurate system for detecting errors in procedural tasks is crucial for supporting human needs in daily life, as it can provide instant

arXiv:2606.24825v1 Announce Type: new Abstract: Part-of-Speech (POS) tagging is a foundational NLP task underpinning machine translation, information extraction, and syntactic parsing. Despite Marathi

arXiv:2606.23943v1 Announce Type: new Abstract: Tokenization is a foundational step in NLP pipelines, yet standard evaluation metrics such as fertility rate fail to capture morphological correctness f

arXiv:2606.21366v2 Announce Type: replace-cross Abstract: This work examines sexualised AI-generated English-speaking voices offered by a popular commercial platform. New technologies may enable sexua

arXiv:2606.22974v2 Announce Type: replace Abstract: Recent work on preference elicitation in large language models (LLMs) has demonstrated that, when given a series of choices between two outcomes, LL

arXiv:2603.02370v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) have grown increasingly powerful in recent years, but can also exhibit harmful biases. Prior studies investigat

arXiv:2606.22780v1 Announce Type: new Abstract: Mental illnesses among drug users are an increasing international issue, particularly in regions where early detection cannot be easily undertaken. The

arXiv:2606.11419v1 Announce Type: new Abstract: Most existing drone-based inspection systems require the drone to fly dangerously close to the target or follow complex flight paths to capture small de

arXiv:2602.20958v2 Announce Type: replace-cross Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) frameworks aid human search tasks by detecting and recognizing specific individuals, then trackin

arXiv:2606.11217v1 Announce Type: cross Abstract: The proliferation of large language models (LLMs) and autonomous AI agents has given rise to a rapidly growing methodological paradigm: 'in silico' be

arXiv:2512.11393v2 Announce Type: replace Abstract: Humans can intuitively parallelise complex activities, but can a model predict this from observing a single person? Given one egocentric video, we i

arXiv:2606.10092v1 Announce Type: new Abstract: Decision-making under risk is typically studied through single-shot lottery choices. Yet many real decisions involve combinatorial risk, where risk aris

arXiv:2606.10459v1 Announce Type: cross Abstract: Nowadays, social media networks have become widely preferred sources of information. Especially during the time of the Coronavirus disease 2019 COVID

arXiv:2510.07061v2 Announce Type: replace Abstract: While automatic metrics drive progress in Machine Translation (MT) and Text Summarization (TS), existing metrics have been developed and validated a

arXiv:2606.10039v1 Announce Type: new Abstract: We consider the nonprehensile object transportation task known as the waiter's problem, in which a robot must move an object balanced on a tray from one

arXiv:2510.20182v2 Announce Type: replace Abstract: Pedestrian simulation traditionally relies on expert-tuned, hand-crafted models that limit scalability and generalization. Meanwhile, large-scale vi

arXiv:2606.06857v1 Announce Type: new Abstract: A central goal of cognitive neuroscience is to characterize the features that are represented by human language cortex. Artificial language models (LMs)

arXiv:2606.06794v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) successfully grounds large language model (LLM) outputs in trusted documents, but factual grounding alone is insuff

arXiv:2606.07172v1 Announce Type: cross Abstract: Geospatial understanding is a critical yet underexplored dimension in the development of machine learning systems for tasks such as image geolocation

arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesir

arXiv:2606.06177v1 Announce Type: new Abstract: Speech translation (ST) is increasingly adopted in user applications, yet its evaluation largely focuses on decontextualized testbeds and holistic quali

arXiv:2606.05660v1 Announce Type: new Abstract: Embodied AI systems are increasingly expected to reason and act over extended horizons in physical environments. This growing capability brings safety t

arXiv:2606.02973v1 Announce Type: new Abstract: Are utterances by AI chatbots meaningful? Concretely, if a user asks, say, Anthropic's agent Claude, 'What is the capital of Spain?' and Claude answers,

arXiv:2606.03142v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) show strong visualization interpretation, yet it is unclear whether their responses reflect genuine reasoning over

arXiv:2606.01171v1 Announce Type: cross Abstract: Artificial intelligence (AI) can reproduce and amplify the structural inequities faced by minoritized communities. Participatory AI has been proposed

arXiv:2606.00712v1 Announce Type: new Abstract: The CASTLE Challenge @ EgoVis 2026 evaluates long-form egocentric video question answering over 600+ hours of multi-perspective recordings. Each four-ch

arXiv:2208.00967v4 Announce Type: replace Abstract: Graph-based models have achieved great success in person re-identification tasks recently, which compute the graph topology structure (affinities) a

arXiv:2606.01282v1 Announce Type: new Abstract: Text-to-Image (TTI) systems are now everyday infrastructure for journalism, education, advertising, and public communication, and the demographic and cu

arXiv:2510.00481v2 Announce Type: replace-cross Abstract: In 2025, Large Language Model (LLM) services have launched a new feature -- AI video chat -- allowing users to interact with AI agents via rea

arXiv:2606.00990v1 Announce Type: new Abstract: A mobile robot following a graph of known routes can make costly navigation errors when a temporary obstacle blocks a critical edge: waiting too long be

arXiv:2501.04661v3 Announce Type: replace-cross Abstract: The web-scale of pretraining data has created an important evaluation challenge: to disentangle linguistic competence on cases well-represente

arXiv:2605.30444v1 Announce Type: new Abstract: Recent advances in 4D Human-Object Interaction (HOI) generation have enabled increasingly realistic motion synthesis, particularly for single-object man

arXiv:2605.31480v1 Announce Type: new Abstract: Do neural models, such as Large Language Models, genuinely acquire compositional abilities for interpretation of natural language? When we talk about se

arXiv:2511.08548v2 Announce Type: replace Abstract: The evolution of mathematics is shaped importantly by interestingness: researchers choose which problems to pursue, and students choose which proble

arXiv:2605.27441v1 Announce Type: cross Abstract: Query understanding in large-scale industrial search systems is typically implemented as a cascade of disparate, task-specific components. While indiv

arXiv:2307.06240v2 Announce Type: replace-cross Abstract: The Drone Swarm Search project is an environment, based on extsc{PettingZoo}, that is to be used in conjunction with multi-agent (or single-ag

arXiv:2605.26397v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in decision-making tasks where they can amplify or suppress perspectives, raising concerns in high-

arXiv:2605.27050v1 Announce Type: new Abstract: We present BhashaSetu, a linguistically enriched English--Marathi parallel dataset addressing persistent data limitations in low-resource neural machine

arXiv:2603.13373v3 Announce Type: replace-cross Abstract: In ubiquitous and mobile health systems, computational models infer human states from wearable, behavioral, and physiological sensing data. In