Knowledge catalogue
arXiv:2602.00238v2 Announce Type: replace-cross Abstract: Existing retrieval-augmented generation (RAG) systems often assume that each query has a single correct answer. This assumption overlooks open
arXiv:2606.07642v1 Announce Type: new Abstract: Assessing built-environment interaction, such as wheelchair accessibility, is difficult because real-world mobility is shaped by distributed, context-de
arXiv:2606.07756v1 Announce Type: new Abstract: Accurate distance estimation for small drones in long-range imagery is important for tracking and situational awareness, yet remains challenging due to
arXiv:2606.08035v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a leading paradigm for enhancing visual reasoning in Multimodal Large Language Mode
arXiv:2606.09081v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) object detection requires compact detectors that retain small-object details under onboard computation and memory constrai
arXiv:2606.09477v1 Announce Type: new Abstract: Estimating the relative poses of multi-camera systems is a fundamental problem in computer vision, with critical applications in autonomous vehicles, mo
arXiv:2606.07999v1 Announce Type: new Abstract: Effective skill grounding is essential for deploying reusable skills in embodied agents, as even minor embodiment or environmental differences can rende
arXiv:2606.07571v1 Announce Type: cross Abstract: Key-value (KV) caching for shared prefixes is essential for high-throughput large language model (LLM) serving, but it faces critical challenges in em
arXiv:2504.18451v2 Announce Type: replace Abstract: Rapid global population growth underscores the need for digitally enabled agricultural systems that support sustainable food production and data-dri
arXiv:2606.09208v1 Announce Type: new Abstract: During warhead detonation, high-density, high-speed, and mutually occluded fragments are generated. Their mechanical parameters (position, velocity, kin
arXiv:2606.08497v1 Announce Type: new Abstract: As deep language models (DLMs) are increasingly deployed in high-stakes domains such as healthcare, understanding their decision rationale becomes param
arXiv:2606.08167v1 Announce Type: cross Abstract: Recent research has established empirical scaling laws to predict model performance on multi-domain data mixtures. However, a theoretical understandin
arXiv:2606.08612v1 Announce Type: new Abstract: Facial Expression Recognition (FER) has advanced rapidly over the last decade, driven by the shift from handcrafted descriptors and shallow classifiers
arXiv:2606.07645v1 Announce Type: cross Abstract: The scarcity of hard negative samples in current vision-language datasets significantly hinders fine-grained perception. To address this, we propose F
arXiv:2606.09079v1 Announce Type: cross Abstract: Conventional LLMs keep the full KV cache loaded during decoding, causing a severe GPU memory bottleneck for ultra-long context serving. In this report
arXiv:2606.07572v1 Announce Type: cross Abstract: Despite Japan being one of the world's largest advanced democracies, the development of election forecasting models for its national elections remains
arXiv:2606.08308v1 Announce Type: new Abstract: Predicting the generalization performance of deep neural networks without relying on hold-out validation data is a fundamental challenge in machine lear
arXiv:2606.08191v1 Announce Type: cross Abstract: Token aggregation is a common bottleneck in models that map token representations to sample-level predictions, yet most pooling methods operate only i
arXiv:2603.03292v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit high reasoning capacity in medical question-answering, but their tendency to produce hallucinations and o
arXiv:2606.07951v1 Announce Type: cross Abstract: Humans increasingly turn to Language Models (LMs) in ways that shape beliefs and drive decisions, including discussing, rewriting, and summarizing inf
arXiv:2606.08932v1 Announce Type: cross Abstract: Rule-following agents tasked with executing policies and regulations often fail via Silent Scope Omission (SSO): a model applies a general rule but si
arXiv:2606.09551v1 Announce Type: cross Abstract: Two-server secure inference allows a client to query a hosted large language model (LLM) without revealing prompts or embeddings. Recent GPU systems b
arXiv:2606.09453v1 Announce Type: new Abstract: Biochemical recurrence (BCR) after radical prostatectomy is a critical endpoint in prostate cancer, yet risk stratification relies almost entirely on va
arXiv:2606.08799v1 Announce Type: cross Abstract: We study the generalization of ridge-regularized nonlinear least-squares models via on-average algorithmic stability, deriving error bounds for local
arXiv:2606.09681v1 Announce Type: new Abstract: Eye movements, including saccades, are widely regarded as highly sensitive and objective biomarkers of neurophysiologic states. Detecting saccadic signa
arXiv:2606.08844v1 Announce Type: new Abstract: As autonomous systems expand from capital-intensive robotaxis to cost-sensitive logistics, sensor configurations are increasingly optimized for coverage
arXiv:2606.08450v1 Announce Type: new Abstract: Financial portfolio trading is naturally formulated as a reinforcement learning problem, where an agent sequentially rebalances assets under changing ma
arXiv:2601.18585v2 Announce Type: replace Abstract: Fine-tuning-based adaptation is widely used to customize diffusion-based image generation, leading to large collections of community-created adapter
arXiv:2606.08036v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in academic research workflows, but scholarly tasks require high factual precision and therefore ex
arXiv:2606.09432v1 Announce Type: new Abstract: Modeling interacting dynamical systems requires capturing spatial interactions alongside long-range temporal dependencies. Graph neural networks (GNNs)
arXiv:2606.07619v1 Announce Type: new Abstract: We present a Graph Neural Network (GNN) framework for the classification of finite groups according to their solvability. Using graph representations as
arXiv:2606.09105v1 Announce Type: new Abstract: Generating novel, feasible, and high-quality research ideas is an important yet challenging task in scientific discovery.Recent Large Language Model (LL
arXiv:2606.08610v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a powerful paradigm for robot learning, particularly in sim-to-real settings, but its broader adoption remains
arXiv:2606.08403v1 Announce Type: cross Abstract: Text-centered prompt-injection defenses assume that the malicious signal is visible in one of the inspected text views. We study a reproducible LLM01-
arXiv:2606.07703v1 Announce Type: cross Abstract: Long-context prefill remains expensive because full/GQA layers still score the historical sequence, even in hybrid models with local, sparse, linear,
arXiv:2606.08164v1 Announce Type: new Abstract: MRI preprocessing defines the input distribution seen by brain MRI foundation models, yet it is usually treated as routine data cleaning rather than a m
arXiv:2606.08051v1 Announce Type: new Abstract: Financial transaction processing requires extracting structured merchant information from noisy, abbreviated bank transaction strings at scale. Our curr
How do you prove the business value of generative AI to your teams? Technology and finance leaders need to show the clear business value of AI projects to secure ongoing funding. While measuring retur
arXiv:2606.08714v1 Announce Type: cross Abstract: Multirotors are widely used in applications ranging from surveillance to precision agriculture, yet conventional designs remain limited by their under
arXiv:2606.09746v1 Announce Type: cross Abstract: With AI increasingly deployed in safety-critical systems, providing formal robustness guarantees for the underlying models is essential. Existing veri
A developer created a Windows GUI tool for managing and benchmarking different llama.cpp builds, addressing the needs of AMD GPU users who work with multiple compute backends like Vulkan, ROCm, and HI
arXiv:2606.09154v1 Announce Type: new Abstract: Decentralized SGD is a fundamental algorithm in decentralized learning, although the influence of an underlying network topology on its convergence beha
arXiv:2601.05261v2 Announce Type: replace-cross Abstract: Online consumer reviews are important decision-support resources in e-commerce, yet the increasing volume of reviews often creates information
arXiv:2603.08630v2 Announce Type: replace Abstract: We derive integral formulas that simplify the Vector Signal Tensor Product recently introduced by Xie et al., which generalizes the Gaunt tensor pro
arXiv:2606.09558v1 Announce Type: cross Abstract: Motivation: Transformer-based models are increasingly applied to large-scale single-cell transcriptomics, showing strong performance through self-supe
arXiv:2606.09289v1 Announce Type: new Abstract: Understanding tactical organisation of association football, hereafter referred to as football, requires identifying distinct match phases. Yet in-posse
arXiv:2606.07616v1 Announce Type: cross Abstract: Scaling laws provide a fundamental framework for understanding the performance of Language Models (LMs), yet deriving them requires prohibitively expe
arXiv:2606.07651v1 Announce Type: cross Abstract: Traditional fake news detection methods are falling behind as multimodal misinformation grows more advanced, seamlessly blending deceptive text, manip
arXiv:2606.07686v1 Announce Type: cross Abstract: Physics-Informed Neural Network (PINN) is a way of including knowledge in the form of equations in Machine Learning methods. Beyond equations, knowled
arXiv:2606.09099v1 Announce Type: new Abstract: Autonomous UAV swarms require scalable coordination mechanisms that maintain mission performance under limited communication, environmental uncertainty,
arXiv:2601.15423v2 Announce Type: replace Abstract: We introduce Lattice, a hybrid sequential prediction system that conditionally activates learned behavioral structure using binary confidence gating
arXiv:2606.07908v1 Announce Type: new Abstract: Derivative-controlled networks based on ChainzRule (CR) combine cubic polynomial layers with a lightweight forward-mode per-layer Jacobian penalty (DREG
arXiv:2606.08131v1 Announce Type: cross Abstract: Conversational AI is increasingly used for advice, interpretation, reassurance, and decision support in contexts where users may be vulnerable, uncert
arXiv:2606.08170v1 Announce Type: new Abstract: With the evolution of large foundation models (LFMs), data-driven autonomous driving has made significant strides. However, existing paradigms still fac
arXiv:2606.08751v1 Announce Type: new Abstract: Accurate quantification and uptake measurement in PET are critical for assessing disease progression and supporting clinical decision-making. While high
arXiv:2606.07601v1 Announce Type: cross Abstract: We introduce the Laplace-Fourier Neural Operator (LFNO), a unified framework for modeling dynamical systems across transient and steady-state regimes
arXiv:2606.09489v1 Announce Type: new Abstract: Objective: Conformance checking in healthcare seeks to assess whether patient care pathways adhere to clinical guidelines. However, its practical applic
arXiv:2606.08676v1 Announce Type: cross Abstract: AI coding assistants have significantly improved developer productivity by automatically suggesting code that aligns with user intent, and many of the
arXiv:2606.09313v1 Announce Type: new Abstract: Retrieval algorithms are used to estimate atmospheric concentrations of greenhouse gases (GHGs), such as carbon dioxide (CO2) and methane (CH4), by solv
arXiv:2511.18676v2 Announce Type: replace-cross Abstract: Current vision-language models (VLMs) in medicine are primarily designed for categorical question answering (e.g., 'Is this normal or abnormal