Knowledge catalogue
arXiv:2608.11245v1 Announce Type: new Abstract: Online education offers unprecedented scalability and accessibility to global learners from diverse backgrounds, but it often suffers from low engagemen
arXiv:2608.11246v1 Announce Type: new Abstract: The success of coding agents has established the harness as a paradigm: what an agent achieves depends not on the model alone, but on the infrastructure
arXiv:2509.24235v2 Announce Type: replace Abstract: This paper proposes an optimization-based task and motion planning framework, named 'Logic Network Flow,' that integrates temporal logic specificati
arXiv:2608.12057v1 Announce Type: new Abstract: Feature selection is one of the most important and fundamental tasks in data mining, tackled by a family of methods with an established set of evaluatio
arXiv:2608.11829v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as a promising post-training technique for enhancing LLM reasoning. It is commonly believed to enable the stu
arXiv:2608.11236v1 Announce Type: cross Abstract: Roleplay evaluation should do more than assign a single score: it should reveal which role requirements were tested, which failed, and which dialogue
arXiv:2608.11415v1 Announce Type: cross Abstract: Large language models are being proposed as agents in scientific workflows, in domains where no downstream verifier exists. Such deployment assumes th
arXiv:2608.11785v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for financial analysis and trading, but direct trading remains challenging because the predicti
arXiv:2608.11638v1 Announce Type: cross Abstract: Spatially continuous quantification of forest above-ground biomass (AGB) is what makes carbon accounting credible and mitigation strategies actionable
arXiv:2608.11223v1 Announce Type: cross Abstract: Entry-only automatic fare collection systems record boardings but not alightings, preventing direct construction of origin-destination (OD) matrices.
arXiv:2603.24567v2 Announce Type: replace-cross Abstract: Constrained optimization in high-dimensional black-box settings is difficult due to expensive evaluations, the lack of gradient information, a
arXiv:2608.11860v1 Announce Type: cross Abstract: Data-driven inverse design enables efficient generation of nanophotonic structures with prescribed optical responses, but spectrum-to-geometry mapping
arXiv:2312.00114v3 Announce Type: replace Abstract: Event cameras are a novel type of biologically inspired vision sensor known for their high temporal resolution, high dynamic range, and low power co
arXiv:2604.03924v2 Announce Type: replace-cross Abstract: Goal-oriented conversational systems require making sequential decisions under uncertainty about the user's intent, where the algorithm must b
arXiv:2608.11280v1 Announce Type: cross Abstract: Skin cancer diagnosis from dermoscopic images remains challenging due to high intra-class variability, inter-class similarity, class imbalance, and th
arXiv:2608.11288v1 Announce Type: cross Abstract: Assessing catheter and tube placement on chest X-rays is safety-critical yet tedious and error-prone. Current deep learning methods either classify pl
arXiv:2608.12027v1 Announce Type: cross Abstract: Pairwise constrained clustering typically relies on hard must-link/cannot-link labels, whereas realistic pairwise supervision may be real-valued and e
arXiv:2608.12155v1 Announce Type: new Abstract: Vision foundation models have recently emerged as powerful feature extractors for detecting AI-generated images, achieving strong generalization across
arXiv:2608.11585v1 Announce Type: cross Abstract: Physical computing systems exploit device dynamics for computation, but their gradient-based optimization is challenging: backpropagation through a di
arXiv:2603.08131v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) localizes objects from natural-language descriptions in 3D scenes and is fundamental to embodied AI applications. A
arXiv:2608.11752v1 Announce Type: new Abstract: Talking-video character replacement requires coordinated transfer of appearance and voice while preserving the source motion, scene, linguistic content,
arXiv:2608.11410v1 Announce Type: new Abstract: Offline reinforcement learning (RL) offers considerable promise for optimizing ICU treatment decisions, yet standard evaluation metrics Mean Squared Err
arXiv:2608.11840v1 Announce Type: cross Abstract: Growing demand for artificial intelligence (AI) inference services requires scalable infrastructure, yet centralized serving costs rise with demand. W
arXiv:2608.12282v1 Announce Type: new Abstract: Agents deployed in enterprise settings must reason across structured APIs and document collections, yet existing benchmarks evaluate these capabilities
arXiv:2608.11251v1 Announce Type: cross Abstract: Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act. Traditional approaches often do not take into
arXiv:2608.11435v1 Announce Type: new Abstract: Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informa
arXiv:2608.12246v1 Announce Type: cross Abstract: Evaluating security vulnerability detection tools requires benchmark datasets with vulnerability-inducing commits (VICs) - the commits that first intr
arXiv:2608.11592v1 Announce Type: new Abstract: Closed-track testing plays a fundamental role in the verification and validation of automated driving systems (ADS), particularly for safety-critical sc
arXiv:2606.19985v2 Announce Type: replace Abstract: Occlusion-robust scene recovery remains a major challenge in computational imaging, particularly where dense vegetation severely limits visibility.
arXiv:2603.17450v2 Announce Type: replace-cross Abstract: Sequential Recommendation (SR) in multimodal settings typically relies on small frozen pretrained encoders, which limits semantic capacity and
arXiv:2608.11425v1 Announce Type: new Abstract: Underwater image restoration consists of recovering an image which looks like there is no water present. To date, evaluation has not been systematic. Th
arXiv:2608.11777v1 Announce Type: new Abstract: Driving in the real world is open-world: a car may encounter a fallen mattress, a deer, or other objects outside its training data. Naming them is not e
arXiv:2608.11240v1 Announce Type: new Abstract: Vector quantization is an old problem but has recently become central to AI infrastructure. It is therefore experiencing a surge of renewed engineering
arXiv:2608.11883v1 Announce Type: new Abstract: Multimodal satellite imagery provides complementary information for Earth Observation, but accurately combining heterogeneous sensors remains challengin
arXiv:2602.14419v2 Announce Type: cross Abstract: This paper reformulates Transformer/Attention mechanisms in Large Language Models (LLMs) through measure theory and frequency analysis, theoretically
arXiv:2608.11342v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) is a standard approach for adapting LLMs to a target distribution, but in settings such as personalization, where each au
arXiv:2608.11560v1 Announce Type: new Abstract: Personalizing marketing messages with contextual multi-armed bandits (CMABs) drives real business value, yet the objective that ultimately matters - a d
arXiv:2608.11403v1 Announce Type: new Abstract: Self-consistency (SC) via majority vote is a widely used way to spend inference-time compute: sample N chains of thought, return the plurality answer. O
arXiv:2608.11715v1 Announce Type: cross Abstract: The reliability of Large Language Models (LLMs) for API calling degrades in multilingual settings. A common failure occurs when a model selects the co
arXiv:2608.11843v1 Announce Type: new Abstract: The Seungjeongwon Ilgi, a UNESCO Memory of the World record, is only 37.4% translated, and the most conspicuous failure mode in automatic translation is
arXiv:2608.12150v1 Announce Type: new Abstract: Standard evaluation of large language models assumes stable model rankings across inference conditions. We challenge this assumption by varying the toke
arXiv:2608.11649v1 Announce Type: new Abstract: As users increasingly turn to Large Language Models (LLMs) for information and advice on political matters, particularly during election periods, the po
arXiv:2608.11256v1 Announce Type: new Abstract: Institutions use commercial AI detectors for academic integrity, yet detectors cannot distinguish AI editing from full LLM drafts and may treat both as
arXiv:2512.15211v4 Announce Type: replace Abstract: Infrared and visible image fusion is a pivotal technology in low-altitude Unmanned Aerial Vehicle (UAV) reconnaissance missions, enabling robust tar
arXiv:2608.11676v1 Announce Type: new Abstract: Heterogeneous multi-agent LLM systems, where agents are powered by different model families, can outperform homogeneous configurations by reducing redun
arXiv:2608.11446v1 Announce Type: new Abstract: This paper presents a comparative study of two distinct approaches, XGBoost and Long-Short Term Memory (LSTM), for forecasting transmitted heat energy i
arXiv:2608.12276v1 Announce Type: new Abstract: High-fidelity image generation faces a trade-off between speed and quality. Diffusion models produce strong visuals but require costly iterative samplin
arXiv:2608.11663v1 Announce Type: new Abstract: Open-vocabulary change detection (OVCD) enables the identification of user-specified land-cover changes in bitemporal remote sensing images, but existin
arXiv:2608.11050v1 Announce Type: cross Abstract: Deep learning systems perform mainly within the 2D for a single image domain and take the face as a single-dimension representation, losing sight of t
arXiv:2608.10107v1 Announce Type: new Abstract: Emerging World-Action Models (WAMs) have demonstrated promising performance in autonomous driving by jointly modeling future driving scene evolution and
arXiv:2602.06811v3 Announce Type: replace Abstract: Butterfly-inspired flapping-wing robots use broad compliant wings and low-frequency actuation, but pronounced wingbeat-synchronous body dynamics and
arXiv:2608.11053v1 Announce Type: cross Abstract: The application of computer vision in agriculture has shown significant potential for improving crop monitoring and precision farming. However, many e
arXiv:2608.10203v1 Announce Type: new Abstract: Despite the success of convolutional neural networks in image classification tasks and their general application in multi-modal models, their susceptibi
arXiv:2608.10939v1 Announce Type: cross Abstract: Multilingual short-text classification supports operational systems such as content moderation, customer support routing, and intent recognition, yet
arXiv:2608.10978v1 Announce Type: new Abstract: Optical music recognition (OMR) transcribes music scores into digital formats. While the field has advanced significantly on monophonic and piano-form s
arXiv:2606.14498v2 Announce Type: replace-cross Abstract: Predicting the Kohn-Sham Hamiltonian with machine learning can accelerate density functional theory while retaining access to molecular orbita
arXiv:2608.10760v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has become the de-facto interface for connecting LLM agents to enterprise tools, and adoption has been explosive: wit
arXiv:2608.10245v1 Announce Type: cross Abstract: Inventory and distribution planning in Physical Internet networks requires coordinating factory-hub assignments, factory supply, lateral transshipment
arXiv:2608.10588v1 Announce Type: cross Abstract: Purpose: Fine-grained handshape recognition supports computational sign-language transcription, recognition, and translation, but broad, phonetically
arXiv:2608.10470v1 Announce Type: new Abstract: Fair representation learning with a continuous sensitive attribute S requires a representation Z that is statistically independent of S. Existing criter