Search: “labs”

arXiv:2608.14976v1 Announce Type: new Abstract: Text-to-image models are typically reported on average-case prompts, which understates the gap between systems on compositionally demanding requests inv

arXiv:2608.16111v1 Announce Type: cross Abstract: Retrosynthesis is a cornerstone of drug discovery and organic synthesis. While data-driven deep learning models have shown remarkable progress, they a

arXiv:2608.15326v1 Announce Type: new Abstract: Artificial intelligence (AI) benchmarks are not neutral tools of evaluation but socio-technical artefacts that shape competition, power, and research pr

arXiv:2608.15861v1 Announce Type: new Abstract: Fine-grained wrist activity recognition can support applications such as procedural step guidance and context-aware assistance, yet acquiring labeled da

arXiv:2511.22651v2 Announce Type: replace-cross Abstract: Optimization methods have long advanced many fields, yet they struggle when faced with design problems where the search space and design param

arXiv:2608.10512v1 Announce Type: new Abstract: Low-light imaging often introduces color bias caused by the low signal-to-noise ratio and the image formation process. Although recent low-light image e

arXiv:2608.08860v1 Announce Type: cross Abstract: Robotic neural-thread placement requires regulating the insertion-tool tip relative to tissue that moves with cardiac and respiratory pulsation. This

arXiv:2608.06640v1 Announce Type: cross Abstract: The widespread integration of AI coding assistants offers undeniable boosts to engineering velocity. Yet, recent studies point to a growing trade-off,

arXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class

arXiv:2607.18056v2 Announce Type: replace Abstract: Frontier large language models (LLMs) are increasingly integrated into scientific workflows, yet their growing biological capabilities may outpace c

arXiv:2607.11785v2 Announce Type: replace Abstract: Indoor robotics research increasingly uses micro-UAV platforms whose airframes, electronics, and control software are open to modification. Off-the-

arXiv:2608.05120v1 Announce Type: new Abstract: Kinetic model discovery is a central challenge in chemical engineering, as accurate rate expressions are essential for understanding and controlling che

arXiv:2608.05086v1 Announce Type: new Abstract: Language models differ in how safely they behave and these differences are measured by safety benchmarks. But aggregated benchmark scores are hard to tr

arXiv:2608.02663v1 Announce Type: cross Abstract: Accurate ICU mortality prediction requires modeling irregular clinical observations across heterogeneous entity types. Existing sequence models handle

arXiv:2608.02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and inco

arXiv:2608.01724v1 Announce Type: new Abstract: Group conversations are fundamental to human collaboration, yet standard large language models (LLMs) still struggle with the complexities of multi-part

arXiv:2608.02376v1 Announce Type: cross Abstract: Search and database engines still store text as UTF-8, a format built for humans. But the systems that increasingly read and write that text (embedder

arXiv:2607.29274v1 Announce Type: cross Abstract: Claims that language models homogenise are usually measured against human judgements collected for the study, which makes the human side an artifact o

arXiv:2606.13952v2 Announce Type: replace-cross Abstract: Active Motor Noise Cancellation (AMNC) is a noise-reduction feature shipped in commercial fused deposition modeling (FDM) 3D printers. Because

arXiv:2607.26580v1 Announce Type: new Abstract: With the increase in the number of cases related to respiratory diseases, there is an urgent need to detect them early and diagnose them accurately. Con

arXiv:2607.25283v1 Announce Type: new Abstract: This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes th

arXiv:2510.23942v2 Announce Type: replace Abstract: We describe a theory and implementation of an intuitionistic decentralized framework for causal discovery using judo calculus, which is formally def

arXiv:2607.22342v1 Announce Type: new Abstract: The development of effective urban climate adaptation strategies requires comprehensive spatial information on rooftops and buildings, since such inform

arXiv:2607.22255v1 Announce Type: new Abstract: The segmentation of multiple degradations has been a challenging problem in the field of image segmentation. Existing level set approaches commonly adop

arXiv:2607.21004v1 Announce Type: new Abstract: Recently, cross-domain few-shot facial expression recognition (CF-FER) has received considerable attention. However, the performance of existing CF-FER

arXiv:2607.20560v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RA

arXiv:2510.15236v2 Announce Type: replace Abstract: Contemporary AGI evaluations report multidomain capability profiles, yet they typically assign symmetric weights and rely on snapshot scores. This c

arXiv:2607.18135v1 Announce Type: cross Abstract: Learning-based approaches to locomotion have risen in popularity in recent years, showing the capability for complex legged locomotion and whole-body

arXiv:2607.18504v1 Announce Type: cross Abstract: Benchmarks for Geospatial Foundation Models (GFMs) increasingly rank models by aggregate score, but such rankings obscure why models differ: how much

arXiv:2607.18365v1 Announce Type: cross Abstract: Reinforcement learning (RL) for legged robots is advancing locomotion, demonstrating its ability to adapt to new and challenging terrain. Traditionall

arXiv:2602.07643v2 Announce Type: replace Abstract: Foundation models have emerged as a transformative paradigm in 3D medical imaging, with the promise of unified quantitative analysis across diverse

arXiv:2607.13059v1 Announce Type: new Abstract: Data-driven embodied AI is rapidly transitioning into a paradigm that scales training through massively parallel simulation, where GPU-accelerated simul

arXiv:2412.15239v4 Announce Type: replace-cross Abstract: Consumers' engagement with stories is shaped by their expectations about what will happen next, yet modeling these forward-looking beliefs ove

arXiv:2607.12180v1 Announce Type: cross Abstract: An AI teammate's design properties (personality, communication style, when it speaks) can shape a team's trust, coordination, and decisions. Studying

arXiv:2603.00910v2 Announce Type: replace-cross Abstract: Layer-wise capacity in large language models is highly non-uniform: some layers contribute disproportionately to loss reduction, whereas other

arXiv:2607.08098v1 Announce Type: new Abstract: Event cameras offer microsecond temporal resolution, low latency, and high dynamic range, making them attractive for robotics. However, labeled event-ca

arXiv:2607.08227v1 Announce Type: new Abstract: Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structura

arXiv:2607.07883v1 Announce Type: new Abstract: There is relatively little, public, and model-ready data on industrial machinery for African economies. This makes it hard to do quantitative analysis o

arXiv:2607.07368v1 Announce Type: cross Abstract: AI control is a family of techniques to prevent an AI with malicious goals from subverting its operator's intent. AI Control usually studies a single

arXiv:2607.07663v1 Announce Type: new Abstract: AI systems increasingly participate in their own improvement: revising their outputs, adapting their own harnesses during deployment, training on data t

arXiv:2607.03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional

arXiv:2607.02731v1 Announce Type: cross Abstract: Machine learning has demonstrated significant potential for real-time monitoring, optimization, and control of scientific facilities. However, deployi

arXiv:2607.00710v1 Announce Type: cross Abstract: Well-designed autonomous driving datasets have fundamentally shaped research progress, yet existing literature primarily describes what datasets conta

arXiv:2511.19326v2 Announce Type: replace Abstract: Reconstructing biomechanically realistic 3D human motion - recovering both kinematics (motion) and kinetics (forces) - is a critical challenge. Whil

arXiv:2603.29135v2 Announce Type: replace Abstract: Autonomous experimental systems are increasingly used in materials research to accelerate scientific discovery, but their performance is often limit

arXiv:2606.29119v1 Announce Type: cross Abstract: We introduce a pre-registered screening rule that decides, before any implementation, whether an evolutionary / population / lifecycle outer loop over