Knowledge catalogue
arXiv:2610.13862v1 Announce Type: new Abstract: Deploying language-model agents onboard mobile robots requires task reasoning and responsive execution within limited compute and memory. We propose BT-
arXiv:2610.13794v1 Announce Type: new Abstract: Discourse particles subtly shape the flow of discourse by reflecting conversational context and interlocutor attitudes, often leaving the truth-conditio
arXiv:2610.11236v1 Announce Type: new Abstract: Low-cost sensors enable scalable indoor air quality monitoring but require calibration because of nonlinear distortions, noise, and temporal drift. The
arXiv:2610.11678v1 Announce Type: new Abstract: Verifier scores now serve as both benchmark metrics and training rewards for large language model (LLM) agents, and a change in score is routinely read
arXiv:2610.09187v1 Announce Type: new Abstract: Multi-robot task allocators in dynamic missions commonly admit newly released tasks immediately, potentially invoking allocation for each new arrival. W
arXiv:2610.10455v1 Announce Type: new Abstract: Hallucinated information can propagate through multi-stage LLM systems and become part of the context for subsequent reasoning. Existing studies of post
arXiv:2610.08300v1 Announce Type: new Abstract: Long-term conversational memory is becoming an integral component of modern LLM systems. Proposed architectures group records by topics and events, cons
arXiv:2610.05127v1 Announce Type: new Abstract: Physics-informed neural network (PINN) training minimizes a weighted combination of partial differential equation (PDE), boundary-condition, and initial
arXiv:2604.01554v2 Announce Type: replace-cross Abstract: Binary Function Similarity Detection (BFSD) is a core problem in software security, supporting tasks such as vulnerability analysis, malware c
arXiv:2610.04736v1 Announce Type: new Abstract: A pedestrian with a phone could be shown where nearby people will be in the next few seconds, if the forecast stays on the ground while the phone moves,
arXiv:2512.12074v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have emerged as an effective approach for solving partial differential equations (PDEs) by incorporating ph
arXiv:2610.03662v1 Announce Type: new Abstract: Deploying a new decision policy creates a cold-start problem for prediction models whose targets depend on the policy's actions: historical observations
arXiv:2610.00562v1 Announce Type: cross Abstract: Longitudinal clinical reasoning requires large language models (LLMs) to identify and integrate relevant evidence distributed across extended patient
arXiv:2610.01535v1 Announce Type: cross Abstract: Safety routers send each request to one of several models and are judged against the best single model. A major routing benchmark picks that comparato
arXiv:2610.00557v1 Announce Type: cross Abstract: Autonomous red team agents increasingly stress-test AI-enabled cyber defenses by planning strategy and executing multistage attacks. Reinforcement lea
arXiv:2610.00372v1 Announce Type: new Abstract: Large language model agents rely on external harnesses to pass information between the model and its environment and to recover from execution errors. Y
arXiv:2609.38642v1 Announce Type: new Abstract: Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and wit
arXiv:2609.34240v2 Announce Type: replace-cross Abstract: Existing open-ended generation metrics measure likelihood, lexical diversity, or distributional similarity in generic representation space, ye
arXiv:2609.37848v1 Announce Type: new Abstract: Biomedical machine learning papers often compress model performance into one headline number. That number can look like a property of the model even whe
arXiv:2609.33371v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents turn credential hygiene from a storage problem into an execution-security problem. A key pasted into a pr
arXiv:2609.32280v1 Announce Type: new Abstract: Hero frames are in-film stills used as source imagery for theatrical posters, streaming cover art, film database listings, and other promotional placeme
arXiv:2609.35335v1 Announce Type: new Abstract: Machine learning task type identification is essential for constructing valid ML pipelines, yet in practice it is typically specified manually. We inves
arXiv:2609.32160v1 Announce Type: cross Abstract: Typed decision models (TDMs) return probability distributions over caller-defined options without generating text. TypeSafe released Jev, a commercial
arXiv:2609.32318v1 Announce Type: new Abstract: Leaderboards rank long-horizon agents by their final outputs. Yet a higher score alone does not establish whether two systems are comparable or which st
arXiv:2609.30273v1 Announce Type: new Abstract: We investigate how historical data from fixed randomized experiments (A/B tests) can be used to inform the deployment of adaptive experiments based on c
arXiv:2609.28991v1 Announce Type: cross Abstract: Video understanding is increasingly performed by multi-stage LLM agents that separate temporal grounding, visual observation, and reasoning. Yet these
arXiv:2609.30058v1 Announce Type: cross Abstract: AI-assisted job-search tools have become increasingly popular by making it easier to find and apply to jobs. But by making it easier for applicants to
arXiv:2609.29861v1 Announce Type: new Abstract: We investigate whether GPT-6-Astra, a general-purpose foundation model, can navigate unfamiliar environments using its own perception, reasoning, and de
arXiv:2609.28610v1 Announce Type: new Abstract: Benchmarking is an increasingly critical part of research in machine learning and the domains where it is applied, including healthcare. Yet, despite th
arXiv:2609.27143v1 Announce Type: new Abstract: Infrastructure-based radar systems offer robust and long-range solutions for traffic monitoring, yet their detection and tracking performance under real
arXiv:2609.27311v1 Announce Type: cross Abstract: Command-and-control (C2) traffic increasingly hides within TLS, so defenders now apply machine learning to traffic metadata. Many studies assume that
arXiv:2609.26955v1 Announce Type: new Abstract: Fairness audits in production ML typically occur once, at deployment, on a single domain. Both fail in practice: fairness can shift after retraining or
arXiv:2609.23142v1 Announce Type: new Abstract: Building gameplay features in a game engine requires more than code, as code that compiles and runs does not necessarily implement the requested gamepla
arXiv:2607.14109v2 Announce Type: replace Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central
arXiv:2609.25376v1 Announce Type: new Abstract: Post-training quantization reduces the memory requirements of vision-language-action (VLA) models, but precision selection must account for the interact
arXiv:2609.25709v1 Announce Type: new Abstract: Environmental reconnaissance needs mobile platforms that carry sensors, preserve measurement context, and return interpretable evidence under limited en
arXiv:2609.24088v1 Announce Type: new Abstract: In latent generative models, reconstruction quality is often assumed to correlate with generative performance. However, reconstruction FID (rFID) can ex
arXiv:2509.08494v2 Announce Type: replace-cross Abstract: As humans delegate more tasks and decisions to artificial intelligence (AI), we risk losing control of our individual and collective futures.
arXiv:2609.22375v1 Announce Type: cross Abstract: Introduction. Open collaborative knowledge graphs such as Wikidata increasingly ground agentic artificial intelligence, information retrieval, and lan
arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative co
arXiv:2609.22603v1 Announce Type: new Abstract: Summarization ships in countless production systems, making model selection a routine decision that depends on measuring summary quality. Existing metri
arXiv:2609.21793v1 Announce Type: cross Abstract: Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, b
arXiv:2609.21259v1 Announce Type: new Abstract: Understanding and modeling human intelligence are parallel goals shared by artificial intelligence (AI) and cognitive science. As AI systems grow increa
arXiv:2609.19210v1 Announce Type: cross Abstract: Graph neural networks are widely used for transductive node classification, with accuracy typically measured on randomly drawn train/validation/test s
arXiv:2609.19879v1 Announce Type: new Abstract: Question answering has advanced rapidly with large language models, but predominantly for high-resource languages, in both text and spoken settings. Spo
arXiv:2609.17578v1 Announce Type: cross Abstract: Let a_1,ldots,a_m be distinct elements of a field K, and let Z(X)=prod_{i=1}^m (X-a_i). We study the arithmetic complexity of computing the unique nor
arXiv:2609.17540v1 Announce Type: new Abstract: We propose a framework that transfers tacit human subjective criteria to robotic systems for the appropriate grasping of deformable objects. Achieving s
arXiv:2609.08171v2 Announce Type: replace Abstract: Low-latency simultaneous speech-to-speech translation must keep pace with ongoing speech while preserving key information. To meet these demands, sy
arXiv:2609.14765v1 Announce Type: cross Abstract: Hip exoskeletons may improve recovery from unexpected gait perturbations, yet personalizing assistance remains difficult because balance is multidimen
arXiv:2609.15144v1 Announce Type: new Abstract: Purpose: Paired pre- and post-operative photographs are the standard unit of evidence for plastic surgical outcomes, yet no objective metric verifies wh
arXiv:2609.13265v1 Announce Type: cross Abstract: Near-infrared (NIR) imaging does not consistently outperform standard color cameras for daytime agricultural traversability once spatial data leakage
arXiv:2609.14290v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in healthcare imaging pipelines for diagnostic support, and training-time attacks against them are a
arXiv:2609.10855v1 Announce Type: new Abstract: Vision-language models (VLMs) enable robotic per- ception by associating visual observations with natural-language concepts. Yet their performance in co
arXiv:2609.09945v1 Announce Type: new Abstract: Machine learning-based credit scoring is increasingly central to Peer-to-Peer (P2P) lending, yet its resilience to adversarial manipulation, where appli
arXiv:2609.08599v1 Announce Type: new Abstract: Large Language Model (LLM) agents are evolving from single-session tools toward long-term personal assistants that must adapt to individual users across
arXiv:2609.05933v1 Announce Type: new Abstract: Efficiency is increasingly important for Large Language Model (LLM)-based multi-agent systems (MAS), as larger models and more agents introduce substant
arXiv:2609.04603v1 Announce Type: new Abstract: Recent generative image-editing Diffusion Transformers (DiTs) demonstrate impressive semantic editing capabilities but still struggle with spatially con
arXiv:2609.04390v1 Announce Type: cross Abstract: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 30% of the general population. Ultrasound-based imaging, includ
arXiv:2609.03900v1 Announce Type: new Abstract: Continual knowledge-updating methods are often declared superior from one final checkpoint and one conventional adapter rank. We show that this can be i
arXiv:2609.03189v1 Announce Type: cross Abstract: This article presents a structured framework of behavioral indicators that may signal progression toward potentially catastrophic threats from artific