Knowledge catalogue
arXiv:2605.03304v1 Announce Type: new Abstract: The European Union's Carbon Border Adjustment Mechanism (CBAM) creates a complex challenge for the interconnected European electricity market. Tradition
arXiv:2605.00856v1 Announce Type: cross Abstract: Accurate and continuous estimation of cognitive workload is fundamental to creating adaptive human-machine systems. However, designing architectures t
arXiv:2503.12001v4 Announce Type: replace Abstract: The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Tra
arXiv:2605.01920v1 Announce Type: cross Abstract: Large language models are increasingly used within larger systems ('LLM agents'). These make a sequence of LLM calls, each call providing the LLM with
arXiv:2601.10915v2 Announce Type: replace-cross Abstract: In the emerging paradigm of edge learning, neural networks (NNs) are partitioned across distributed edge devices that collaboratively perform
arXiv:2605.00926v1 Announce Type: new Abstract: The Receiver Operating Characteristic (ROC) curve of a binary classifier has often been utilized to measure the performance of the classifier. The area
arXiv:2605.02525v1 Announce Type: new Abstract: Autonomous indoor mobile robots can navigate reliably to metric coordinates using established frameworks such as ROS 2 Navigation 2, yet they lack the a
arXiv:2603.18066v2 Announce Type: replace-cross Abstract: Backpropagation has enabled modern deep learning but is difficult to realize as an online, fully distributed hardware learning system due to g
arXiv:2605.00838v1 Announce Type: cross Abstract: In mobile telecommunications, alarms act as early warning signals. They are triggered when a cell, the basic unit of radio coverage, shuts down or beh
arXiv:2605.00880v1 Announce Type: new Abstract: Autonomous driving (AD) is evolving towards end-to-end (E2E) frameworks through two primary paradigms: monolithic models exemplified by Vision-Language-
arXiv:2605.01778v1 Announce Type: new Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network a
arXiv:2605.00425v1 Announce Type: new Abstract: Reinforcement learning (RL) has significantly advanced the ability of large language model (LLM) agents to interact with environments and solve multi-tu
arXiv:2605.01888v1 Announce Type: new Abstract: Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything
arXiv:2605.00276v1 Announce Type: new Abstract: Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible itineraries, as interacting
arXiv:2605.01355v1 Announce Type: new Abstract: Automated leaf disease classification is critical for early disease detection in resource-constrained field environments. Vision Transformers (ViTs) pro
arXiv:2605.00582v1 Announce Type: cross Abstract: Expectations about the support of artificial intelligence (AI) may influence interaction outcomes similar to placebos. Such expectations may result fr
arXiv:2605.01098v1 Announce Type: cross Abstract: Adversarial examples in machine learning are typically generated using gradients, obtained either directly through access to the model or approximated
arXiv:2605.01544v1 Announce Type: new Abstract: Imitation learning (IL) has seen remarkable progress, yet field deployment of IL-powered robots remains hindered by the challenge of out-of-distribution
arXiv:2605.02259v1 Announce Type: new Abstract: Incomplete propagation data significantly hinders robust fake news detection. Recent approaches leverage large language models to simulate missing user
arXiv:2605.02107v1 Announce Type: new Abstract: A team of mobile robots monitors spatially distributed processes and delivers measurements to a base, where AoI is measured from sensing start, capturin
arXiv:2605.02651v1 Announce Type: cross Abstract: Scientific peer review increasingly struggles to assess reproducibility at the scale and complexity of modern research output. Evaluating reproducibil
arXiv:2603.14643v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strong general capabilities, but their deployment in high-stakes domains is hindered by their opacity and
arXiv:2605.02200v1 Announce Type: new Abstract: Online advertising governance faces significant challenges due to the non-stationary nature of regulatory policies, where emerging mandates (e.g., restr
arXiv:2506.03820v2 Announce Type: replace Abstract: Hausa texts are often characterized by writing anomalies, such as incorrect character substitutions and spacing errors, which sometimes hinder natur
arXiv:2605.02402v1 Announce Type: new Abstract: Reflective thinking is a key competency in education, but assessing reflective writing remains a time-consuming and subjective task for education expert
arXiv:2512.10571v4 Announce Type: replace Abstract: Recent advancements in video generation highlight that realistic audio-visual synchronization is crucial for engaging content creation. However, exi
arXiv:2602.07200v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as informat
arXiv:2507.21803v2 Announce Type: replace Abstract: Carbon Capture and Storage (CCS) stands as a pivotal technology for fostering a sustainable future. The process, which involves injecting supercriti
arXiv:2605.02620v1 Announce Type: new Abstract: Reproducing an empirical NLP study used to take weeks. Given the released data and a modern agentic-research harness, we redo every experiment of a rece
arXiv:2605.01074v1 Announce Type: cross Abstract: Associative memory or content-addressable memory is an important component function in computer science and information processing, and at the same ti
arXiv:2605.02520v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) offers a well-established path to grounding large language model (LLM) outputs in external knowledge, yet the quest
arXiv:2401.16764v5 Announce Type: replace Abstract: Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary para
arXiv:2311.10320v3 Announce Type: replace Abstract: Data collected by different modalities can provide a wealth of complementary information, such as hyperspectral image (HSI) to offer rich spectral-s
arXiv:2605.02124v1 Announce Type: new Abstract: Softmax-routed mixture-of-experts models approach hard routing as the temperature tends to zero, but this limit is singular near routing ties. This pape
arXiv:2605.02263v1 Announce Type: new Abstract: Recent diffusion large language models (dLLMs) have demonstrated both effectiveness and efficiency in reasoning via a block-based semi-autoregressive ge
arXiv:2605.01242v1 Announce Type: new Abstract: Reinforcement learning (RL) is a fundamental framework for sequential decision-making, in which an agent learns an optimal policy through interactions w
arXiv:2508.19932v2 Announce Type: replace Abstract: The proliferation of digital payment platforms has transformed commerce, offering unmatched convenience and accessibility globally. However, this gr
arXiv:2603.11907v2 Announce Type: replace Abstract: Estimating Individual Treatment Effects (ITE) in multi-treatment scenarios faces two critical challenges: the Hyperparameter Selection Dilemma for b
arXiv:2605.01634v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) offer a flexible paradigm for solving differential equations by embedding governing laws into the training obje
arXiv:2605.01277v1 Announce Type: new Abstract: Recently, Convolutional Neural Network (CNN) or Transformer architecture based models have been proposed to overcome the limitations of Recurrent Neural
arXiv:2408.04596v2 Announce Type: replace Abstract: In this work, we use language modeling to investigate the factors that influence insertional code-switching. Code-switching occurs when a speaker al
arXiv:2605.02153v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mappi
arXiv:2605.01479v1 Announce Type: new Abstract: Latent-based diffusion model watermarking embeds watermarks into generated images' latent space to enable content attribution, offering a training-free
arXiv:2605.01309v1 Announce Type: new Abstract: Long-tailed distributions are common in real-world recognition tasks, where a few head classes have many samples while most tail classes have very few.
arXiv:2605.01989v1 Announce Type: new Abstract: Distributed machine learning (ML) training has become a necessity with the prevalence of billion to trillion-parameter-scale models. While prior work ha
arXiv:2605.02348v1 Announce Type: new Abstract: Large language models pick up social biases from the data they are trained on and carry those biases into downstream applications, often reinforcing ste
arXiv:2605.01858v1 Announce Type: new Abstract: Streaming video understanding requires processing unbounded video streams with limited memory and computation, posing two key challenges. First, continu
arXiv:2605.00849v1 Announce Type: cross Abstract: Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant
arXiv:2407.13278v3 Announce Type: replace Abstract: Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other dat
arXiv:2605.02245v1 Announce Type: new Abstract: Automated sleep stage classification typically employs a single population-agnostic model, disregarding established demographic variations in sleep arch
arXiv:2605.00894v1 Announce Type: new Abstract: Vision foundation models (VFMs), such as DINOv3, provide rich semantic representations that are promising for computational pathology. However, many cur
arXiv:2605.02752v1 Announce Type: new Abstract: Open-world text-guided class-agnostic counting (CAC) has emerged as a flexible paradigm for counting arbitrary object classes by using natural language
arXiv:2601.15416v2 Announce Type: replace Abstract: Sparse-view Cone-Beam Computed Tomography reconstruction from limited X-ray projections remains a challenging problem in medical imaging due to the
arXiv:2410.08491v2 Announce Type: replace Abstract: Automated vehicles promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains cha
arXiv:2605.01024v1 Announce Type: new Abstract: Multimodal Emotion Recognition (MER) is critical for interpreting real-world interactions. While Multimodal Large Language Models (MLLM) have shown prom
arXiv:2605.02073v1 Announce Type: new Abstract: Mathematical reasoning is a key benchmark for large language models. Reinforcement learning is a standard post-training mechanism for improving the reas
arXiv:2605.00950v1 Announce Type: cross Abstract: Monitoring high-dimensional engineering structures in extreme environments is limited by non-stationary excitation, nonlinear structural kinematics, a
arXiv:2605.01484v1 Announce Type: new Abstract: With the rapidly improving reasoning abilities of Large Language Models (LLMs), there is also a rising demand to use them in a wide variety of domains.
arXiv:2605.02519v1 Announce Type: new Abstract: Classic Network Intrusion Detection Systems (NIDS) often rely on manual feature engineering to extract meaningful patterns from network traffic data. Ho
arXiv:2605.01432v1 Announce Type: new Abstract: Autonomous landing in cluttered or unstructured environments remains a safety-critical challenge for unmanned aerial vehicles (UAVs), particularly under