Knowledge catalogue
arXiv:2607.24785v1 Announce Type: cross Abstract: Efficient exploration of the photonic crystal (PhC) lattice design space is essential for developing photonic crystal surface-emitting lasers. While c
arXiv:2601.18260v3 Announce Type: replace Abstract: In clinical radiology, accurate patient table positioning is essential to align specific internal organs of interest with the scanner imaging isocen
arXiv:2408.03291v4 Announce Type: replace Abstract: Vision Transformers (ViTs) have gained significant attention, but their high computing cost limits the practical applications. While post-training q
arXiv:2607.24893v1 Announce Type: cross Abstract: Multi-agent LLM systems can be attacked by a payload that no single agent ever holds in full: a poisoned tool hides encrypted fragments in its observa
arXiv:2507.11548v3 Announce Type: replace-cross Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias re
arXiv:2607.26034v1 Announce Type: new Abstract: Technological races create tension between speed and safety: actors may gain by moving faster than competitors, even when risky development is harmful.
arXiv:2607.25146v1 Announce Type: new Abstract: The distance between persons reveals significant information about their perception of each other. However, such information is not easily extractable a
arXiv:2607.24805v1 Announce Type: cross Abstract: AI Engram (Kwon et al., 2026) formalizes the four engram criteria of neuroscience as a constrained inverse problem in weight space and solves it close
arXiv:2607.25503v1 Announce Type: new Abstract: Computational cytology on whole-slide images is challenging because malignant cells are rare, heterogeneous, and annotated slides are scarce. Anomaly de
arXiv:2607.25147v1 Announce Type: new Abstract: Trajectory data collected in real-world settings is frequently incomplete due to sensor failure, communication loss, or occlusion. We address the task o
arXiv:2607.25228v1 Announce Type: new Abstract: Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and
arXiv:2607.25543v1 Announce Type: cross Abstract: Generative AI has rapidly expanded audio-visual forgery beyond human-centric deepfakes into general scenes. Existing AIGC detection methods assume aud
arXiv:2607.25197v1 Announce Type: new Abstract: Sleep staging remains challenging due to long-range temporal dependencies, ambiguous stage transitions-particularly in N1-and substantial distribution s
arXiv:2505.24539v4 Announce Type: replace-cross Abstract: We present a study on how and where personas -- defined by distinct sets of human characteristics, values, and beliefs -- are encoded in the r
arXiv:2508.14003v4 Announce Type: replace-cross Abstract: The H-theorem provides a microscopic foundation for the Second Law of Thermodynamics and therefore occupies a central place in statistical phy
arXiv:2607.25090v1 Announce Type: new Abstract: Machine learning engineering (MLE) tasks require long-horizon decision making over iterative solution debugging and refinement, under expensive and feed
arXiv:2403.07598v2 Announce Type: replace Abstract: In this paper, we present Mondrian, an edge system that enables high-performance object detection on high-resolution video streams. Many lightweight
arXiv:2607.25107v1 Announce Type: cross Abstract: Security and privacy are primordial requirements for Federated Learning (FL), especially in fields such as healthcare and genomics where sensitive inf
arXiv:2607.25612v1 Announce Type: new Abstract: Perception tasks for autonomous vehicles need to work satisfactorily in adverse weather conditions. Due to lack of real-world weather datasets, weather
arXiv:2607.25667v1 Announce Type: cross Abstract: Psychotherapists need repeated training and supervision by experts; however, scalability is problematic. Here we present MyMentorLLM, a multimodal voi
arXiv:2509.06893v2 Announce Type: replace-cross Abstract: Motile nanosized particles, or 'nanobots', promise more effective and less toxic targeted drug delivery because of their unique scale and prec
arXiv:2607.25108v1 Announce Type: cross Abstract: Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, pro
arXiv:2607.25719v1 Announce Type: new Abstract: We propose Dynamic Constraint Learning (DCL), a data-driven framework for constrained optimization when constraint functions are unknown and cannot be q
arXiv:2607.18060v2 Announce Type: replace Abstract: Long-horizon robotic tasks require diverse capabilities that no single policy can reliably provide. Heterogeneous policies offer complementary stren
arXiv:2607.25122v1 Announce Type: new Abstract: Search Trajectory Networks (STNs) are a graph-based tool for visualizing and characterizing the behavior of optimization algorithms. STNs' reliance on d
arXiv:2607.25219v1 Announce Type: new Abstract: Social navigation has progressed from simplified 2D environments toward a more general vision-based setting, in which a robot needs to achieve socially
arXiv:2604.14990v2 Announce Type: replace Abstract: The prospect of Artificial General Intelligence (AGI) is increasingly driving institutional decisions, and alignment of AGI is a hard problem. The c
arXiv:2607.17761v2 Announce Type: replace-cross Abstract: Recently, speech deepfake detection (SDD) has achieved significant progress. However, its robustness evaluation remains largely confined to co
arXiv:2607.25914v1 Announce Type: new Abstract: Autonomous Network Levels 4-5 require AI agents to invoke tools across vendor boundaries without human oversight, yet existing management standards lack
arXiv:2607.25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources. That pressur
arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r
arXiv:2509.10847v3 Announce Type: replace-cross Abstract: As artificial intelligence (AI) companions become capable of human-like communication, including telling jokes, understanding how people cogni
arXiv:2607.24223v1 Announce Type: new Abstract: Relevance is a query-dependent estimate of whether a document or excerpt contains useful evidence. Existing retrieval agents use relevance to select top
Across eight case studies spanning industry and academia, we explore what this shift means for scientific computing—and why human verification, stewardship, and long-term maintenance matter. https://o
arXiv:2607.23882v1 Announce Type: new Abstract: Modern System-on-Chip (SoCs) often contain hundreds of millions to tens of billions of gates, making existing Hardware Trojan (HT) detection methods imp
Learn how to build trustworthy AI agent evals using regression tests, capability evals, production traces, LLM judges, and reproducible environments. The post AI agent evaluation: Tips from Anthropic
arXiv:2607.22867v1 Announce Type: cross Abstract: Optical scattering has conventionally been regarded as an impediment in imaging research due to the degradation of image quality during reconstruction
arXiv:2607.24384v1 Announce Type: new Abstract: Electric joint systems are significant elements of an underwater manipulator for its actuation, drive, and control. Working in an underwater environment
arXiv:2602.04266v2 Announce Type: replace-cross Abstract: Aortic valve disease (AVD) represents a major public health burden, while its diagnosis relies on echocardiography, which is limited by cost a
arXiv:2607.23586v1 Announce Type: new Abstract: Long-lived AI agents increasingly evolve after deployment by retaining experience, acquiring skills and tools, revising workflows, delegating work, and
arXiv:2607.24608v1 Announce Type: new Abstract: This work investigates uncertainty decomposition and explainability in a deep learning-based framework for gyroscope bias correction. A 1-D Convolutiona
arXiv:2607.24568v1 Announce Type: new Abstract: Learned feature reweighting can improve automatic modulation classification (AMC) in software, but the same operation introduces additional arithmetic a
arXiv:2607.24272v1 Announce Type: cross Abstract: The vast chemical design space and complex, interdependent design variables make catalyst discovery for targeted properties highly labor- and resource
arXiv:2603.28371v2 Announce Type: replace-cross Abstract: When an agent can articulate why something works, we typically take this as evidence of genuine understanding. This presupposes that effective
arXiv:2607.22662v1 Announce Type: new Abstract: Open-web corpora curated via highly selective filters, such as FineWeb-Edu and DCLM, constitute the core of LLM pretraining data and have significantly
arXiv:2607.23524v1 Announce Type: new Abstract: Deep search is becoming a core capability of modern agent systems, yet it is typically evaluated solely based on end-to-end answer accuracy. This couple
arXiv:2607.16692v2 Announce Type: replace-cross Abstract: The increasing complexity of modern software systems has made automated code generation a fundamental task in software engineering. However, e
arXiv:2607.23442v1 Announce Type: new Abstract: LLM debate is usually evaluated by final answers, but transcripts also reveal whether later turns develop new argumentative content or return to earlier
arXiv:2607.23845v1 Announce Type: new Abstract: Other-initiated Self-repair, or in short Other-initiated Repair (OIR), is an essential mechanism in conversational interaction, whereby a recipient sign
arXiv:2607.24126v1 Announce Type: cross Abstract: Brain-machine interfaces provide a link between neural activity and external devices, enabling restoration of motor function and advancing human-machi
arXiv:2607.24210v1 Announce Type: new Abstract: In clinical oncology studies, metastatic cancer is commonly evaluated using 'Response Evaluation Criteria in Solid Tumors' (RECIST), in which the diamet
arXiv:2607.24453v1 Announce Type: cross Abstract: Learning from minimal human supervision is a long-standing goal in medical image analysis, where dense expert annotations are costly. We study retinal
arXiv:2603.00408v2 Announce Type: replace-cross Abstract: We present an Ising-compatible framework for formal neural-network robustness verification under bounded input perturbations. For piecewise-li
arXiv:2607.22569v1 Announce Type: new Abstract: Coding agents are increasingly integrated into system operations, where their tool use can directly modify project artifacts, execution environments, an
arXiv:2607.23997v1 Announce Type: new Abstract: The ever-growing adoption of Artificial Intelligence (AI) creates the need to deploy Deep Neural Networks in a variety of computational environments. We
arXiv:2506.03168v2 Announce Type: replace Abstract: Amid the challenges posed by global population growth and climate change, traditional agricultural Internet of Things (IoT) systems is currently und
arXiv:2506.10292v2 Announce Type: replace-cross Abstract: Training deep learning networks with minimal supervision has gained significant research attention due to its potential to reduce reliance on
arXiv:2607.24168v1 Announce Type: new Abstract: Road crashes remain among the gravest threats to public safety, and preventing them is a defining task of transportation systems worldwide. Much of that
arXiv:2511.04666v4 Announce Type: replace Abstract: A fundamental challenge in developing general learning algorithms is their tendency to forget past knowledge as they adapt to new data. Addressing t
arXiv:2607.24532v1 Announce Type: new Abstract: Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by ad