Knowledge catalogue
arXiv:2505.19763v3 Announce Type: replace Abstract: The seminal breakthrough of AlphaFold in protein structure prediction relied on a learned potential energy function parameterized by deep models, in
arXiv:2505.01595v2 Announce Type: replace-cross Abstract: We present a state-of-the-art model for fine-grained probability estimation of propositions conditioned on context. Recent advances in large l
arXiv:2604.23018v1 Announce Type: cross Abstract: Web-scale 3D asset collections are abundant, but rarely deployment-ready. Assets ship with arbitrary metric scale, incorrect pivots and forward axes,
arXiv:2604.23909v1 Announce Type: new Abstract: Navigational aids for blind and low vision individuals struggle conveying dynamic real-world environments, leading to cognitive overload from continuous
arXiv:2604.24331v1 Announce Type: new Abstract: Research on video-based eye-tracking has long explored stereo and glint-based methods, yet existing wearable eye trackers - both commercial and open-sou
arXiv:2604.23666v1 Announce Type: cross Abstract: Line current differential relays (LCDRs) are measurement-driven relays that rely on time-synchronized multi-phase current waveforms to infer internal
arXiv:2604.24355v1 Announce Type: new Abstract: This article explores the progress made in the creation of a pilot activated recovery system (PARS) for advanced jet trainers that utilizes artificial i
arXiv:2604.23290v1 Announce Type: cross Abstract: Active learning algorithms automatically identify the most informative samples from large amounts of unlabeled data and tremendously reduce human anno
arXiv:2604.24117v1 Announce Type: new Abstract: Efficient job-shop scheduling with transportation resources is critical for high-performance manufacturing. With the rise of 'decentralized factories',
arXiv:2604.24403v1 Announce Type: new Abstract: This article evaluates an artificial intelligence (AI)-based Automatic Ground Collision Avoidance System (AGCAS) designed for advanced jet trainers to e
arXiv:2604.23327v1 Announce Type: new Abstract: Active perception is a fundamental problem in autonomous robotics in which the robot must decide where to move and what to sense in order to obtain the
arXiv:2604.23361v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on a wide range of software engineering tasks, including code generation and analysi
arXiv:2604.23954v1 Announce Type: new Abstract: Artificial Intelligence and Machine Learning (AI/ML) models used in clinical settings are increasingly deployed to support clinical decision-making. How
arXiv:2604.24076v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed in high-stakes and operational settings, evaluation strategies based solely on aggregate accur
arXiv:2604.22777v1 Announce Type: new Abstract: Fault diagnosis of general aviation aircraft faces challenges including scarce real fault data, diverse fault types, and weak fault signatures. This pap
arXiv:2604.23195v1 Announce Type: cross Abstract: Analog circuit design relies heavily on reusing existing intellectual property (IP), yet searching across heterogeneous representations such as SPICE
arXiv:2604.23072v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly tasked with complex real-world analysis (e.g., in financial forecasting, scientific discovery), yet t
arXiv:2404.10141v2 Announce Type: replace-cross Abstract: Text-to-image (T2I) models have achieved remarkable progress in high-quality image synthesis, yet most benchmarks rely on simple, self-contain
arXiv:2604.22964v1 Announce Type: new Abstract: Anemia affects over one billion people globally and remains severely under-diagnosed in low-resource regions where laboratory blood tests are inaccessib
arXiv:2509.16702v2 Announce Type: replace Abstract: Personalized animal image generation is challenging due to rich appearance cues and large morphological variability. Existing approaches often exhib
arXiv:2602.10139v3 Announce Type: replace-cross Abstract: Mobile Graphical User Interface (GUI) agents have demonstrated strong capabilities in automating complex smartphone tasks by leveraging multim
arXiv:2512.09972v5 Announce Type: replace-cross Abstract: Navigating the capability--efficiency trade-off in Large Language Models (LLMs) requires approximating a high-quality Pareto set. Existing mod
arXiv:2604.23615v1 Announce Type: cross Abstract: This paper studies interpretable and fair artificial intelligence architectures for understanding English reading. Introduced transformer-based models
arXiv:2604.22816v1 Announce Type: cross Abstract: AI-enhanced interference rejection in radio frequency (RF) transmissions has recently attracted interest because deep learning approaches trained on b
arXiv:2604.23418v1 Announce Type: new Abstract: Uniform random rotations are a useful primitive in applications such as fast Johnson-Lindenstrauss embeddings, kernel approximation, communication-effic
arXiv:2604.23459v1 Announce Type: cross Abstract: Multi-agent systems (MAS), composed of networks of two or more autonomous AI agents, have become increasingly popular in production deployments, yet i
arXiv:2604.24353v1 Announce Type: cross Abstract: The continuous advancement of autonomous driving (AD) introduces challenges across multiple disciplines to ensure safe and efficient driving. One such
arXiv:2604.23124v1 Announce Type: cross Abstract: As software systems grow in complexity, they must satisfy an increasing number of competing quality attributes, making it essential to balance them in
arXiv:2604.23449v1 Announce Type: new Abstract: Argumentation is a core practice in STEM education, but its productivity depends on who participates and how they interact. Higher-achieving students of
arXiv:2604.22766v1 Announce Type: cross Abstract: In this report, we review the current state of methodologies to forecast the arrival of artificial general intelligence, assess their reliability, and
arXiv:2604.24086v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models have been demonstrated possessing strong zero-shot generalization for robot control, their massive parameter
arXiv:2604.22856v1 Announce Type: new Abstract: Accurate vehicle detection is a critical component of autonomous driving, traffic surveillance, and intelligent transportation systems. This paper prese
arXiv:2604.22841v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) aims to assess the recognition utility of face samples and is essential for reliable face recognition (FR) systems.
arXiv:2604.23284v1 Announce Type: cross Abstract: In this work, we present Au-M-ol, a novel multimodal architecture that extends Large Language Models (LLMs) with audio processing. It is designed to i
arXiv:2604.22821v1 Announce Type: cross Abstract: Voice assistants increasingly rely on Speech Language Models (SpeechLMs) to interpret spoken queries and execute complex tasks, yet existing benchmark
arXiv:2604.23542v1 Announce Type: new Abstract: Wildfires are an escalating global concern due to the devastating impacts on the environment, economy, and human health, with notable incidents such as
arXiv:2604.22786v1 Announce Type: new Abstract: We present AutoCompress, a transformer compression method motivated by an empirical finding: in small transformers, Layer 0 carries disproportionately h
arXiv:2604.23518v1 Announce Type: cross Abstract: Existing theory suggests that Kolmogorov-Arnold Networks (KANs) can overcome the spectral bias commonly observed in neural networks under the assumpti
arXiv:2604.24441v1 Announce Type: new Abstract: Autonomous agents capable of navigating Graphical User Interfaces (GUIs) hold the potential to revolutionize digital productivity. However, achieving tr
arXiv:2604.23430v1 Announce Type: cross Abstract: The relentless expansion of scientific literature presents significant challenges for navigation and knowledge discovery. Within Research Information
arXiv:2604.22937v1 Announce Type: new Abstract: Verification is becoming central to both reinforcement-learning-based training and inference-time control of large language models (LLMs). Yet current v
arXiv:2604.22871v1 Announce Type: cross Abstract: Automated red-teaming methods for large language models typically optimize attack prompts within a fixed, human-designed strategy, leaving the attack
arXiv:2510.18346v2 Announce Type: replace Abstract: Audio-Visual Question Answering (AVQA) requires models to effectively utilize both visual and auditory modalities to answer complex and diverse ques
arXiv:2604.22869v1 Announce Type: cross Abstract: In many cyber-physical systems, especially in critical applications such as aeroplanes, data to train anomaly detection and diagnosis algorithms is la
arXiv:2604.24685v1 Announce Type: new Abstract: Chromosome analysis is a fundamental step in the diagnosis of genetic diseases, but the manual karyotyping workflow is time-consuming and heavily depend
arXiv:2601.06166v2 Announce Type: replace Abstract: Accelerated dynamic volumetric magnetic resonance imaging (4DMRI) is essential for applications relying on motion resolution. Existing 4DMRI produce
arXiv:2503.02107v2 Announce Type: replace Abstract: Most autonomous vehicles rely on accurate and efficient localization, which is achieved by comparing live sensor data to a preexisting map, to navig
arXiv:2604.24428v1 Announce Type: cross Abstract: Electroencephalography (EEG) is highly susceptible to artifact contamination, such as electrooculographic (EOG) and electromyographic (EMG) interferen
arXiv:2512.07868v2 Announce Type: replace-cross Abstract: Bayesian optimization is widely used for optimizing expensive black box functions, but most existing approaches focus on scalar responses. In
arXiv:2601.22925v2 Announce Type: replace-cross Abstract: Recent years have seen a rapid surge in research leveraging Large Language Models (LLMs) for recommendation. These methods typically employ su
arXiv:2604.22762v1 Announce Type: cross Abstract: Contemporary product analytics systems require users to pose explicit queries, such as writing SQL, configuring dashboards, or constructing funnels, b
arXiv:2601.18840v3 Announce Type: replace Abstract: Markov decision problems are most commonly solved via dynamic programming. Another approach is Bellman residual minimization, which directly minimiz
arXiv:2509.21979v4 Announce Type: replace-cross Abstract: Visual language models (VLMs) have the potential to transform medical workflows. However, the deployment is limited by sycophancy. Despite thi
arXiv:2603.03555v2 Announce Type: replace-cross Abstract: As multi-agent Large Language Model (LLM) systems scale, evaluating their emergent coordination dynamics becomes increasingly critical. Howeve
arXiv:2604.24679v1 Announce Type: new Abstract: Pathology foundation models (PFMs) have recently emerged as powerful pretrained encoders for computational pathology, enabling transfer learning across
arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit
arXiv:2604.23698v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have shown promise in formal theorem proving, yet evaluating semantic correctness remains challenging. E
arXiv:2511.20006v2 Announce Type: replace-cross Abstract: Automatic Pitch Correction (APC) enhances vocal recordings by aligning pitch deviations with intended musical notes. However, existing APC sys
arXiv:2604.24018v1 Announce Type: new Abstract: This paper studies the problem of robot performance evaluation, focusing on how to obtain accurate and efficient estimates of real-world behavior under
arXiv:2510.17381v2 Announce Type: replace Abstract: Detecting out-of-distribution (OOD) data is critical for machine learning, be it for safety reasons or to enable open-ended learning. However, beyon