Knowledge catalogue
arXiv:2609.19850v1 Announce Type: new Abstract: Actor-critic architecture has been widely used in continuous robot control. However, they rely on learning a value network, introducing additional compu
arXiv:2609.19228v1 Announce Type: new Abstract: Dexterous robot hands must often grasp objects whose shape, size, and pose are known only approximately. Grasp planners typically require accurate objec
arXiv:2609.20481v1 Announce Type: cross Abstract: Conferences, journals, funders, schools, and universities are struggling with a surge of potentially AI-generated submissions from ostensibly human au
arXiv:2609.20321v1 Announce Type: new Abstract: Autonomous vehicles depend entirely on Simultaneous Localization and Mapping (SLAM) to navigate safely in unknown environments. However, relying on a si
arXiv:2609.20614v1 Announce Type: cross Abstract: Frontier AI models are rapidly gaining the ability to exploit vulnerabilities in complex pieces of software. The risk is not theoretical, as evidenced
arXiv:2609.20540v1 Announce Type: new Abstract: Autonomous recovery of a small multirotor onto a hovering multirotor carrier differs from recovery onto ground or shipborne platforms because the recove
arXiv:2609.19347v1 Announce Type: cross Abstract: Robotic additive manufacturing (AM) extends material-extrusion printing beyond gantry kinematics but makes process planning robot-dependent. A slicer-
arXiv:2609.19916v1 Announce Type: cross Abstract: Large language models (LLMs) are typically evaluated on static benchmarks, even though natural language constantly evolves through newly emerging word
arXiv:2609.19717v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable reasoning capabilities by utilizing chain-of-thought (CoT) as a scratchpad for intermediate stag
arXiv:2609.19515v1 Announce Type: new Abstract: Verifier-based selection improves LLM performance by generating multiple candidate solutions and using a verifier to select the most promising one. Howe
arXiv:2609.20318v1 Announce Type: cross Abstract: Testing Autonomous Driving Systems (ADS) requires realistic safety-critical scenarios, but collecting such data from real-world driving is costly and
arXiv:2609.20389v1 Announce Type: cross Abstract: Offline policy evaluation (OPE) is crucial in high-stakes reinforcement learning applications, where new policies must be assessed reliably before dep
arXiv:2609.19947v1 Announce Type: new Abstract: LLM-based AI agents process user requests through iterative reasoning and tool execution, often involving the invocation of remote LLM APIs with local t
arXiv:2609.19709v1 Announce Type: new Abstract: Batched multi-armed bandits update on a service's own schedule, and the usual implementation carries each arm's absolute reward rate from one update to
arXiv:2609.19302v1 Announce Type: new Abstract: Open datasets describing human behavior in environments shared with mobile robots remain limited, particularly for retail activities that combine locomo
arXiv:2609.19358v1 Announce Type: new Abstract: Three-dimensional object detection for autonomous driving is dominated by detectors trained on large corpora of human-annotated 3D boxes. Such a detecto
arXiv:2609.19985v1 Announce Type: cross Abstract: Fine-tuning foundation models on new tasks inevitably suffer from catastrophic forgetting. While existing works attempt to mitigate this on the basis
arXiv:2609.20110v1 Announce Type: new Abstract: Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together
arXiv:2609.20296v1 Announce Type: new Abstract: A myoelectric interface needs calibration from the user before it will function. Earlier work has treated calibration as a quantity, but has not asked t
arXiv:2609.19203v1 Announce Type: new Abstract: AI applications have shifted from single, monolithic foundation models (FM) to compound agentic systems. Yet today's stacks remain fragmented: even as p
arXiv:2609.19657v1 Announce Type: cross Abstract: Repeated prompt prefixes are increasingly common in LLM serving workloads, appearing in system prompts, templated retrieval-augmented generation pipel
arXiv:2609.20123v1 Announce Type: new Abstract: Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalize
arXiv:2609.19243v1 Announce Type: cross Abstract: Spectral co-clustering is a useful tool for discovering latent structure in word-document matrices, but its reliance on singular value decomposition (
arXiv:2609.20594v1 Announce Type: new Abstract: Quantum long short-term memory (QLSTM) models extend recurrent sequence learning with variational quantum circuits, but their optimization behavior can
arXiv:2312.01020v3 Announce Type: replace Abstract: Stock prices forecasting has always been a challenging task. Although many research projects try to address the problem, few of them pay attention t
arXiv:2609.20063v1 Announce Type: cross Abstract: The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security r
arXiv:2609.20629v1 Announce Type: new Abstract: Autonomous recovery of a micro unmanned aerial vehicle (UAV) onto a moving airborne carrier enables reusable deploy-mission-recover operation, but coupl
arXiv:2609.20807v1 Announce Type: new Abstract: Reinforcement learning (RL) of large language models is notoriously sensitive to small differences between training and inference engines, often referre
arXiv:2609.19480v1 Announce Type: new Abstract: The muscles that power insect flight fall into one of two categories: 1) synchronous muscles that contract under direct control from the nervous system,
arXiv:2609.19615v1 Announce Type: cross Abstract: Modern applications generate massive volumes of raw telemetry data, but translating those noisy, heterogeneous event streams into actionable business
arXiv:2609.20475v1 Announce Type: new Abstract: Open-vocabulary scene understanding is fundamental for robotics, laying the groundwork for spatial reasoning and object manipulation. While closed-vocab
arXiv:2609.20086v1 Announce Type: new Abstract: Long-term multivariate time series plays a significant role in many application areas such as power systems, trading, etc. However, their accurate predi
arXiv:2609.20194v1 Announce Type: cross Abstract: Triangular membership functions (MFs) are widely used in fuzzy systems because of their interpretability, low parameterization complexity, and strong
arXiv:2609.20091v1 Announce Type: new Abstract: The Antibandwidth and Cyclic Antibandwidth problems are NP-hard graph labeling problems that aim to maximize the minimum (cyclic) distance between label
arXiv:2609.19418v1 Announce Type: cross Abstract: In evidence-based policymaking, typically one experimental sample is observed, then a learned policy recommendation is implemented at scale. Policies
arXiv:2609.20565v1 Announce Type: new Abstract: Recent advancements in large language models have revolutionized the field of psychological counseling, especially in the context of Cognitive Behaviora
TypeSafe announced Jev on Tuesday: you give it data plus typed questions (yes/no, pick-one, 0–N scale) and it returns a probability for every option, crazy fast. I signed up and then refreshed my inbo
arXiv:2505.03953v3 Announce Type: replace Abstract: When solving optimization problems under uncertainty with contextual data, utilizing machine learning to predict the uncertain parameters' values is
arXiv:2609.20171v1 Announce Type: new Abstract: The support threshold of the Apriori algorithm involves a trade-off in conducting market basket analysis: the associations that occur frequently are not
arXiv:2609.19378v1 Announce Type: new Abstract: Online residual learning can reduce model mismatch in predictive control, but passive data collection may fail to adequately cover states that become im
arXiv:2609.20150v1 Announce Type: new Abstract: Conventional satellite remote sensing transmission follows a reconstruct-then-infer paradigm that optimizes pixel-level fidelity, creating an objective
arXiv:2609.19577v1 Announce Type: new Abstract: Teleoperation, a human-in-the-loop control scheme, allows a human operator to remotely command and guide a mobile robot to navigate in off-road environm
arXiv:2609.20409v1 Announce Type: new Abstract: Two-timescale stochastic approximation (TTSA) is a fundamental tool for analyzing coupled iterative algorithms in reinforcement learning, optimization,
arXiv:2503.24203v3 Announce Type: replace-cross Abstract: Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a
arXiv:2609.20214v1 Announce Type: cross Abstract: Early transformer fault diagnosis is challenged by nonlinear dissolved-gas interactions, overlapping fault signatures, and limited labeled data, while
arXiv:2609.19681v1 Announce Type: new Abstract: Cooperative autonomous driving in the IoT-to-Edge-to-Cloud continuum requires system-level validation across vehicles, infrastructure sensors, edge-side
arXiv:2609.19182v1 Announce Type: new Abstract: Benchmarks are central to how progress in large language models (LLMs) is assessed and communicated. Yet model rankings alone reveal little about how ev
I'm trying to find out whether back-and-forth between two different LLMs improves task success beyond strong alternatives under a controlled resource budget — and I'd rather hear that it's already set
arXiv:2609.20820v1 Announce Type: cross Abstract: Complex robotic manipulation tasks frequently require a long-term memory of past events and actions. As conditioning on full histories renders policie
arXiv:2609.20408v1 Announce Type: cross Abstract: Large language models are usually interpreted through concepts that humans already possess: truthfulness, refusal, deception, personality, harmfulness
arXiv:2609.18610v1 Announce Type: new Abstract: Classical dynamic programming represents optimal sequential decisions through value functions and policies. While this functional representation is natu
arXiv:2609.17565v1 Announce Type: new Abstract: Online handwriting recognition systems typically represent pen trajectories through fixed-length Euclidean shape descriptors that capture the spatial ou
arXiv:2609.18739v1 Announce Type: cross Abstract: Poor quality or noisy annotations in Named Entity Recognition (NER), as in any other NLP task, make it challenging to achieve state-of-the-art perform
arXiv:2609.17731v1 Announce Type: new Abstract: High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management
arXiv:2505.07622v2 Announce Type: replace Abstract: Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metri
arXiv:2609.19144v1 Announce Type: cross Abstract: Direct preference alignment methods are widely used to align large language models (LLMs) with human preferences because of their computational and me
arXiv:2410.22229v2 Announce Type: replace-cross Abstract: Offloading stateful network functions to multi-threaded SoC SmartNICs promises significant performance and cost benefits. However, realizing t
arXiv:2609.18542v1 Announce Type: new Abstract: 4D radar has emerged as a promising next-generation sensor for improving the robustness of autonomous driving perception systems because of its stable s
arXiv:2609.18516v1 Announce Type: new Abstract: While Large Language Models excel in natural language processing, efficiently extending their capabilities to spoken input remains a significant challen
arXiv:2609.18070v1 Announce Type: new Abstract: Vine robots navigate cluttered environments by extending from their tip. Although their ability to operate in such environments has been extensively dem