Knowledge catalogue
arXiv:2604.14306v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated high proficiency on English-centric medical examinations, their performance often declines when fac
arXiv:2604.13059v1 Announce Type: new Abstract: Most dialogue-based electronic medical record (EMR) systems still behave as passive pipelines: transcribe speech, extract information, and generate the
arXiv:2604.12968v1 Announce Type: cross Abstract: Balancing convergence speed, generalization capability, and computational efficiency remains a core challenge in deep learning optimization. First-ord
arXiv:2604.09549v1 Announce Type: cross Abstract: Recommender systems are central to online services, enabling users to navigate through massive amounts of content across various domains. However, the
arXiv:2604.09552v1 Announce Type: cross Abstract: Engineering rulebooks and technical standards contain multimodal information like dense text, tables, and illustrations that are challenging for retri
arXiv:2604.11006v1 Announce Type: new Abstract: 3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshe
arXiv:2604.09430v1 Announce Type: cross Abstract: Text embeddings are central to modern information retrieval and Retrieval-Augmented Generation (RAG). While dense models derived from Large Language M
arXiv:2604.08809v1 Announce Type: new Abstract: Scalable Vector Graphics (SVG) represent visual content as structured, editable code. Each element (path, shape, or text node) can be individually inspe
arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac
arXiv:2602.11635v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved strong performance on perception-oriented tasks, yet their ability to perform mathematical sp
arXiv:2508.07514v3 Announce Type: replace Abstract: Reliable plant species and damage segmentation for herbicide field research trials requires models that can withstand substantial real-world variati
arXiv:2610.20954v1 Announce Type: cross Abstract: Objective. A decoder of imagined speech that works for a new user without calibration would make a non-invasive speech interface practical. We tested
arXiv:2610.20993v1 Announce Type: new Abstract: Reordering multiple-choice options can change a model's answer, an effect studied as selection bias (a preference for certain option letters) and as ord
arXiv:2610.18057v1 Announce Type: new Abstract: Transformers can implement reinforcement-learning algorithms in context, yet how off-policy control emerges within Transformers remains poorly understoo
arXiv:2610.13461v1 Announce Type: new Abstract: AI systems are making rapid progress in mathematics, but this progress is hard to measure. Benchmarks of solved problems saturate, and in benchmarks of
arXiv:2610.08159v1 Announce Type: new Abstract: COMET reports translation quality as a single number, and that number is routinely compared across target languages written in different scripts. Such a
arXiv:2610.08649v1 Announce Type: new Abstract: Video-language models are ranked by multiple-choice accuracy on frames from a uniform grid. The grid has two parameters, a rate and a phase, and benchma
arXiv:2510.13210v2 Announce Type: replace Abstract: We compare Ising ({-1, +1}) and QUBO ({0, 1}) encodings for Boltzmann machine learning under controlled protocols that fix the sampler, optimizer, a
arXiv:2610.02397v1 Announce Type: new Abstract: Electric utilities and grid operators increasingly rely on machine-learning models to forecast next-day demand, and those models learn from meter data t
arXiv:2610.01692v1 Announce Type: new Abstract: Wrist electrodermal activity (EDA) differs in amplitude from one person to the next, so affect-recognition models normalize their input before classific
arXiv:2609.37455v1 Announce Type: new Abstract: High-performance surgical master consoles offer intuitive articulated manipulation but are expensive and difficult to reproduce, while accessible commer
arXiv:2609.36829v1 Announce Type: new Abstract: An executor can respond strongly to a change in a supplied plan's priority while showing a small change in the same information-selection probability wh
arXiv:2609.37494v1 Announce Type: new Abstract: Multiple-choice benchmarks are cheap to grade and are running out of room, and the standard remedy, writing harder items, is slow and repeated for every
arXiv:2609.34198v1 Announce Type: new Abstract: Language-model judges compare agent upgrades with their predecessors, but a fixed judge can make version-dependent mistakes. We analyze 35 public coding
arXiv:2609.33880v1 Announce Type: cross Abstract: Convolutional EEG decoders are trained at a fixed width, usually set by their authors on other data. Growing methods add neurons during training where
arXiv:2609.33179v1 Announce Type: cross Abstract: Constrained-option scoring reads a model's probabilities for a fixed set of permitted answers, so it returns a score even when the model is about to w
arXiv:2609.33189v1 Announce Type: cross Abstract: When the human reference scores zero on a metric, the released GTRS-Dense label generator for NAVSIM marks every candidate trajectory in the scene as
arXiv:2609.31057v1 Announce Type: new Abstract: Geometric filters have recently been introduced to improve the accuracy and consistency of inertial-based integrated navigation systems. Error states we
arXiv:2609.31117v1 Announce Type: new Abstract: Service robots remain difficult to deploy in domestic environments, partly because fully autonomous operation is not yet reliable in unpredictable surro
arXiv:2609.30037v1 Announce Type: new Abstract: Deployment-oriented compression is attractive for resource-constrained brain--computer interfaces (BCIs), but whether it changes adversarial vulnerabili
arXiv:2609.27828v1 Announce Type: cross Abstract: Legacy smart HVAC controllers rely on vendor-cloud TLS secured by ECDH and RSA, both broken by Shor's algorithm, and typical 10-15 year lifespans mean
Just watched a video from three years ago where Matt Berman tested Bard (yes, remember Bard?) and most of the tests were like summarization or logic tests. If it ever came to coding, it was the snake
arXiv:2609.27372v1 Announce Type: cross Abstract: Benchmarks for full-duplex spoken dialogue models score turn-taking with binary fixed-window rules that reward immediate response or silence by comple
arXiv:2609.26854v1 Announce Type: cross Abstract: Sound Scene Generation is about the automatic synthesis of artificial sound scenes. We introduce SsgCaps, a publicly available dataset of human-engine
arXiv:2609.23315v1 Announce Type: cross Abstract: Graph databases are frequently positioned as categorically necessary for connected-data workloads, yet the systems dimension along which they actually
arXiv:2609.26168v1 Announce Type: cross Abstract: Recent work reports that vision--language models (VLMs) struggle to establish and maintain stable reference in repeated reference games. Rather than a
arXiv:2602.18569v2 Announce Type: replace Abstract: Many people could benefit from exoskeleton assistance during gait, for either medical or nonmedical purposes. But exoskeletons bring added mass and
arXiv:2511.04473v3 Announce Type: replace-cross Abstract: Retrieval of information from graph-structured knowledge bases represents a promising direction for improving the factuality of LLMs. While va
arXiv:2505.12254v3 Announce Type: replace Abstract: Existing visual place recognition (VPR) datasets predominantly rely on vehicle-mounted imagery, offer limited multimodal diversity, and underreprese
arXiv:2609.22750v1 Announce Type: new Abstract: Manual attendance methods, such as paper or register-based systems, take a lot of time, can lead to errors, and are easy to falsify. Face recognition is
arXiv:2609.19802v1 Announce Type: new Abstract: Physical teleoperation integrates human cognitive flexibility with robotic precision, yet demanding manipulation tasks frequently induce severe cognitiv
arXiv:2607.16682v2 Announce Type: replace-cross Abstract: The widespread adoption of high-level deep learning libraries, while accelerating model development, has increasingly abstracted away the inte
arXiv:2609.16541v1 Announce Type: cross Abstract: We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements
arXiv:2609.16744v1 Announce Type: new Abstract: The integration of renewable energy sources into the electrical grid introduces complex challenges in fault detection and coordination of grid recovery
arXiv:2609.11286v1 Announce Type: new Abstract: Synthetic relational data is normally produced by a model trained on a real dataset, and its quality is measured as the distance to that dataset. This p
arXiv:2609.09404v1 Announce Type: cross Abstract: Agentic AI frameworks let a language model plan, keep memory, and call tools that reach real files, mail, and services. Most of these agents also read
arXiv:2609.10935v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) try to determine whether a specific record was used to train a model, a privacy risk that matters in natural langu
arXiv:2609.11758v1 Announce Type: new Abstract: Allowing large language models (LLMs) to retrieve information from a set of trusted documents can increase reliability and reduce hallucination. However
arXiv:2609.09429v1 Announce Type: new Abstract: While accurate measurement of socioeconomic indicators remains challenging in data-scarce regions, which limits policy interventions and resource alloca
arXiv:2609.08609v2 Announce Type: replace Abstract: Tracking semantic change in low-resource languages across extensive historical timelines presents significant challenges due to data scarcity and th
arXiv:2609.07884v1 Announce Type: new Abstract: Recent work, such as Vision Banana, shows that lightweight instruction tuning can enable an image generator to achieve state-of-the-art performance acro
arXiv:2609.07981v1 Announce Type: cross Abstract: Audio provenance attribution - which system produced a synthetic utterance - is reported at near-ceiling accuracy on clean benchmarks, yet audio reach
arXiv:2609.04151v1 Announce Type: new Abstract: Generative image models can now produce high-quality images, follow complex instructions, and support precise edits, but they still struggle to preserve
arXiv:2608.29887v1 Announce Type: new Abstract: Multiple-choice question answering (MCQA) benchmarks in NLP use number-right scoring (accuracy), but in educational testing, the scoring scheme, the com
arXiv:2603.18007v2 Announce Type: replace-cross Abstract: The study explores whether current Large Language Models (LLMs) exhibit Theory of Mind (ToM) capabilities -- specifically, the ability to infe
arXiv:2608.27205v1 Announce Type: new Abstract: Nitrogen rates for winter wheat are set before the season, under unknown prices and weather. The standard UK advice does not respond to prices, yet rece
arXiv:2608.22316v1 Announce Type: cross Abstract: Whether an intermediate stage of modern Arabic handwriting helps or hurts historical Arabic HTR is usually decided from one implementation and one com
arXiv:2608.18632v1 Announce Type: new Abstract: Aerial nadir video combines weak geometric constraints with severe perceptual aliasing, making it a difficult regime for monocular SLAM. We benchmark fi
arXiv:2608.14677v1 Announce Type: cross Abstract: Most mobile image-generation applications are thin clients over cloud services, leaving outputs hard to audit. We present an Android latent-diffusion
arXiv:2608.12329v1 Announce Type: cross Abstract: Progress on AI for psychosis-risk assessment is limited by a data-access bottleneck. Real clinical interviews are difficult to share because of privac