Knowledge catalogue
arXiv:2606.23832v1 Announce Type: cross Abstract: The use of dedicated corridors for Advanced Air Mobility (AAM) traffic is one of the most commonly proposed pathways to integrating them into existing
arXiv:2606.24489v1 Announce Type: new Abstract: Pose graph optimization (PGO) is a key back-end component for state estimation in networked multi-robot simultaneous localization and mapping (SLAM). In
arXiv:2606.24219v1 Announce Type: new Abstract: Stochastic quantum neural networks (SQNNs) encode neuronal activations as qubits, synaptic topology as entanglement, and neural noise through a Lindblad
arXiv:2606.23959v1 Announce Type: new Abstract: Because mathematics is highly abstract, a single statement can take very different forms depending on what subfield it is framed in. There are many exam
arXiv:2606.24051v1 Announce Type: new Abstract: Vision-Language-Action driving models convert a pretrained Vision-Language Model into a driving policy, allowing them to use world knowledge and follow
arXiv:2606.24586v1 Announce Type: new Abstract: Deep learning approaches to biometric verification are commonly trained by optimizing indirect objectives, creating a misalignment between the optimizat
arXiv:2606.24047v1 Announce Type: new Abstract: One of the significant mental health issues affecting female sex workers (FSWs) is mental disorders, especially depression. Exposure to violence, stigma
arXiv:2603.03742v2 Announce Type: replace Abstract: Despite the remarkable performance of large language models (LLMs) in text-to-SQL (SQL generation), correctly producing SQL queries remains challeng
arXiv:2606.18941v3 Announce Type: replace-cross Abstract: PLCopen XML defines two encoding formats for IEC 61131-3 Ladder Diagram programs: a textual encoding using elements, and a graphical encoding
arXiv:2606.23870v1 Announce Type: cross Abstract: PLCverif is the most mature open-source platform for PLC formal verification, developed at CERN and in production use since 2019. Yet it has two funda
arXiv:2606.23867v1 Announce Type: new Abstract: The exact computation of the Normalized Maximum Likelihood (NML) codelength for regular non-smooth estimators (e.g., Lasso) has been historically limite
arXiv:2503.12902v4 Announce Type: replace Abstract: Model trees provide an appealing way to perform interpretable machine learning for both classification and regression problems. In contrast to ``cla
arXiv:2606.23758v1 Announce Type: cross Abstract: Domain generalization learns from multiple source domains to generalize to unseen target domains. However, it often neglects the realistic case of lab
arXiv:2606.23871v1 Announce Type: new Abstract: Survival analysis is central to clinical decision-making, yet reliable time-to-event models require large, diverse cohorts that are rarely available at
arXiv:2503.14862v3 Announce Type: replace Abstract: Open-vocabulary detectors are proposed to locate and recognize objects in novel classes. However, variations in vision-aware language vocabulary dat
arXiv:2606.23702v1 Announce Type: cross Abstract: Modulation recognition systems rely on heterogeneous signal representations. 2D signal-image modalities such as time-frequency and cyclostationary map
arXiv:2508.16420v3 Announce Type: replace Abstract: Target-conditioned sequence models provide a simple interface for controllable offline decision making, but the requested target return can be an un
arXiv:2606.17927v2 Announce Type: replace-cross Abstract: Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional multilayer perceptrons by replacing linear w
arXiv:2606.24669v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for planning and sequential decision-making, but prior work often relies on using them as direc
arXiv:2606.24311v1 Announce Type: new Abstract: As large language model (LLM) agents are applied to longer tasks, they increasingly modify workspace state across multiple rounds of iteration. However,
arXiv:2606.24457v1 Announce Type: new Abstract: Recent advances in stereo matching have achieved remarkable accuracy, but often rely on large models, heavy computation, or additional foundation-model
arXiv:2606.17110v2 Announce Type: replace-cross Abstract: Large Language Models are increasingly trained on proprietary or sensitive data, from private healthcare and financial records to user convers
arXiv:2606.24011v1 Announce Type: cross Abstract: A crucial assumption in graph signal processing (GSP) is the existence of an underlying graph that captures the pairwise similarities between nodes, a
arXiv:2606.24248v1 Announce Type: new Abstract: Event-based object Detection (EvDet), as a biologically inspired visual perception paradigm, demonstrates superior performance in scenarios demanding hi
arXiv:2506.10520v5 Announce Type: replace-cross Abstract: Graph-based multi-task learning at billion-scale presents a significant challenge, as different tasks correspond to distinct billion-scale gra
📣📣 Meet Qwen-AgentWorld — a native language world model that simulates 7 agent environments (MCP, Search, Terminal, SWE, Web, OS, Android) within a single model. Environment modeling is the training o
arXiv:2606.24337v1 Announce Type: new Abstract: Czech has been part of Universal Dependencies since its first release in 2015. It has also been one of the best represented languages, with the Prague D
arXiv:2510.24295v2 Announce Type: replace Abstract: As many benchmarks have become saturated, it has become increasingly important to create new datasets that evaluate the generalization capacity of c
arXiv:2606.24078v1 Announce Type: new Abstract: Imitation learning enables robots to acquire complex manipulation skills from demonstrations, but its effectiveness is limited by the cost of collecting
arXiv:2606.24715v1 Announce Type: cross Abstract: We consider the problem of model selection between probabilistic models on data sets of time series. Chosen a proper scoring rule, we denote by the te
arXiv:2606.24366v1 Announce Type: new Abstract: We present MorfFlex, a morphological dictionary architecture suitable for languages with extensive regularity in both inflection and derivation. As the
arXiv:2510.14792v4 Announce Type: replace Abstract: Open-vocabulary object detection (OVD) aims to recognize and localize object categories beyond the training set. Recent approaches leverage vision-l
arXiv:2504.06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have ra
arXiv:2504.17070v3 Announce Type: replace-cross Abstract: Robots need task planning methods to achieve goals that require more than one action. Recently, large pretrained models have demonstrated impr
arXiv:2606.24101v1 Announce Type: cross Abstract: Conventional visual navigation policies often struggle with myopic decision-making and mode collapse in complex environments. While world models offer
arXiv:2606.24381v1 Announce Type: cross Abstract: Prompt-based interaction has become a dominant paradigm for using large language models (LLMs), where multiple candidate prompts are evaluated and the
arXiv:2606.24631v1 Announce Type: new Abstract: The development of trajectory planning strategies for autonomous ground vehicles (AGVs) represents a prevailing research interest within the domain of i
arXiv:2606.24447v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have revolutionized document parsing by enabling end-to-end mapping from images to structured text, imposing a significant
arXiv:2606.24377v1 Announce Type: new Abstract: Compliant joints can embed safety and adaptability into dexterous hands, but achieving large-stroke anthropomorphic motion while maintaining joint-speci
arXiv:2603.20450v2 Announce Type: replace-cross Abstract: A number of scientific conferences and journals have recently enacted policies that prohibit LLM usage by peer reviewers, except for polishing
arXiv:2509.18371v2 Announce Type: replace-cross Abstract: Multi-agent games in dynamic nonlinear settings are challenging due to the time-varying interactions among the agents and the non-stationarity
arXiv:2606.24298v1 Announce Type: cross Abstract: The increasing interest in data-driven methods for power system protection is accompanied by a lack of standardized, publicly available high-voltage w
arXiv:2605.27729v3 Announce Type: replace-cross Abstract: The 2024-2025 Nobel and Turing awards recognised AI and quantum science simultaneously. Yet no deployed system has brought these streams toget
arXiv:2606.17102v2 Announce Type: replace-cross Abstract: Quantum computing promises transformative advances across science and industry, yet the physical hardware that enables these computations rema
arXiv:2606.24403v1 Announce Type: cross Abstract: Object interaction tasks have been a focus of advances in imitation learning. End-to-end methods, dominated by diffusion and flow-based variants have
arXiv:2606.24307v1 Announce Type: cross Abstract: Interactive music and live performance relies on real-time human expression, but modern generative music AI remains largely absent from this domain du
arXiv:2503.05226v2 Announce Type: replace-cross Abstract: Monte Carlo tree search is attractive for robotic manipulation because it can improve action selection through simulation without requiring a
arXiv:2606.24747v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance across a growing range of domains, yet their scale poses deployment challenges in applications w
arXiv:2603.16131v2 Announce Type: replace Abstract: The explosive growth of AI research has created unprecedented information overload, increasing the demand for scientific summarization at multiple l
arXiv:2606.23697v1 Announce Type: cross Abstract: Semantic segmentation of code written in a C-family language remains a challenging problem, due to the language's complex syntax, macro expansion, and
arXiv:2606.24255v1 Announce Type: cross Abstract: Although text-to-motion generation has achieved strong progress in synthesizing realistic single-person motions from language, extending it to text-dr
arXiv:2503.00069v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has focused on producing responses that meet human expectations and align with shared values -
arXiv:2601.18747v2 Announce Type: replace-cross Abstract: Modern AI agents increasingly rely on search infrastructure to execute complex, neuro-symbolic reasoning workflows. These workflows often comp
arXiv:2606.24074v1 Announce Type: cross Abstract: Wang~ite{Wang2026} introduced the Stochastic-Oracle Turing Machine (SOTM) framework and defined token complexity as the minimum expected cost of inter
arXiv:2606.24187v1 Announce Type: new Abstract: Long video understanding remains a daunting challenge for Multimodal Large Language Models (MLLMs) due to the excessive computation and memory footprint
arXiv:2606.24040v1 Announce Type: cross Abstract: MeMo proposes language models with explicit multi-layer correlation matrix memories (CMMs), where memorization, retrieval, and forgetting are architec
arXiv:2606.24279v1 Announce Type: new Abstract: In Description Logics (DLs), reasoning under Rational Closure (RC) is a well-known and widely accepted non-monotonic formalism to handle defeasible know
arXiv:2606.24430v1 Announce Type: cross Abstract: Training of neural networks for histopathology classification tasks typically relies on data encoding into latent space, which reduces complexity and
arXiv:2606.24331v1 Announce Type: new Abstract: Transformer-based language models have become the default substrate for natural language processing and the pace of new releases has made it hard for pr
arXiv:2606.24175v1 Announce Type: new Abstract: While point cloud foundation models have significantly advanced point cloud video understanding, existing parameter-efficient fine-tuning (PEFT) methods