Knowledge catalogue
arXiv:2609.30521v1 Announce Type: new Abstract: Aerial manipulation in outdoor environments remains challenging due to the simultaneous requirements of reliable state estimation, stable aerial motion,
arXiv:2609.31402v1 Announce Type: cross Abstract: Auditory Attention Detection (AAD) utilizes electroencephalographic (EEG) signals to identify a target speaker in a multi-speaker environment. Despite
Agentic AI security is becoming a cross-industry challenge as autonomous systems move among products and platforms. Okta Inc. argues that building trust will require coordinated safeguards rather than
arXiv:2412.20699v3 Announce Type: replace Abstract: Air-ground collaborative robots have shown great potential in the field of fire and rescue. Mapping and navigation, as the key foundation for air-gr
arXiv:2609.30356v1 Announce Type: new Abstract: Cities differ in built form, land cover and development history, complicating comparison across places and time. Satellite foundation models map Earth's
arXiv:2609.30569v1 Announce Type: new Abstract: CryoEM map interpretation requires features that are spatially localized, consistent across samples, and informative across spatial scales. Most deep le
arXiv:2512.06902v2 Announce Type: replace-cross Abstract: As software systems evolve, developers increasingly work across multiple programming languages and often face the need to migrate code from on
arXiv:2609.30751v1 Announce Type: new Abstract: Pairwise language-model judges can gather evidence through direct comparison, reasoning, or reference-based verification, but no single protocol is best
arXiv:2609.31470v1 Announce Type: cross Abstract: Outliers are essential for evaluating and improving the robustness of machine learning systems, especially when future distributions may differ signif
arXiv:2609.31222v1 Announce Type: new Abstract: Pocket-conditioned molecular diffusion updates ambient atom coordinates, but many lead-optimization objectives are expressed on quotient features such a
arXiv:2609.31540v1 Announce Type: cross Abstract: Sending every network-automation input to a third-party frontier LLM exports sensitive artifacts such as production configurations, topologies, and lo
arXiv:2609.30979v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated excellent performance in visual tasks, but their visual causal reasoning capabilities still lack reliabl
arXiv:2609.30708v1 Announce Type: cross Abstract: A key challenge in medical image analysis is the scarcity of large annotated datasets for specific populations and diseases. As deep learning models r
arXiv:2609.30523v1 Announce Type: new Abstract: Large language model (LLM)-powered multi-robot systems are vulnerable to semantic manipulation: an accepted false world-state claim can trigger a fleet-
arXiv:2609.30714v1 Announce Type: new Abstract: Agentic AI systems are increasingly being explored in medical imaging to improve throughput and reduce clinician workload; however, safe deployment rema
arXiv:2609.30947v1 Announce Type: new Abstract: Visual odometry is essential for autonomous navigation in GPS-denied environments, yet RGB-based methods remain vulnerable to motion blur, challenging i
arXiv:2607.11347v2 Announce Type: replace Abstract: Neural networks increasingly inform consequential decisions, making their reliability increasingly important. Yet their internal mechanisms provide
arXiv:2609.31551v1 Announce Type: cross Abstract: Disaggregating the two stages, Prefill and Decode, onto separate GPU pools is now a standard optimization for (text-only) LLM serving. However, multim
arXiv:2609.30417v1 Announce Type: new Abstract: As electric vehicle (EV) adoption increases, ensuring efficient and well-distributed charging infrastructure has become a critical challenge. While many
arXiv:2609.31186v1 Announce Type: new Abstract: Artificial intelligence is advancing rapidly, with increasingly capable systems taking larger roles in reasoning, decision-making, scientific discovery,
arXiv:2609.31514v1 Announce Type: new Abstract: Detectors of AI-generated images are typically trained using samples from all Generative AI architectures they must catch, and struggle as soon as a new
arXiv:2609.31128v1 Announce Type: new Abstract: Frequency-based adversarial attacks have recently grown popular by exploiting spectral sensitivities shared across neural architectures. Unlike spatial
arXiv:2505.14368v3 Announce Type: replace-cross Abstract: Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-sou
arXiv:2609.31473v1 Announce Type: new Abstract: We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from s
arXiv:2609.31154v1 Announce Type: new Abstract: Recent advances in text-to-image (T2I) generation have substantially improved visual synthesis, but have also raised increasing safety concerns due to t
if this takes off, then i was 4 years too early 😭 https://x.com/jerryjliu0/status/1590192512639332353 only OGs remember gpt tree index The entire RAG industry is about to get cooked. Researchers devel
arXiv:2609.31394v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly model visual dynamics and action generation for generalist robot manipulation. A central challenge is to integrate
arXiv:2609.31461v1 Announce Type: new Abstract: Background: Large volumes of unlabeled knee MRI scans are available across repositories but remain insufficiently leveraged. We developed KneePreM, a kn
arXiv:2609.31469v1 Announce Type: cross Abstract: Shapley values, a solution concept from cooperative game theory, have recently become a standard tool for feature credit allocation in machine learnin
arXiv:2602.11229v3 Announce Type: replace Abstract: Reliable physics simulation demands two capabilities that today's neural PDE solvers do not deliver together: generalization across heterogeneous PD
arXiv:2502.01678v5 Announce Type: replace-cross Abstract: Electroencephalography (EEG) provides a non-invasive, highly accessible, and cost-effective approach for detecting Alzheimer's disease (AD). H
arXiv:2609.30498v1 Announce Type: new Abstract: Sequential inference estimates latent states from noisy and incomplete observations. Particle Filters (PFs), a class of Monte Carlo methods based on imp
arXiv:2609.30758v1 Announce Type: new Abstract: Raindrops can cause occlusion and distortion in the background scenes due to their adherence to windows or camera lenses. Existing raindrop removal meth
arXiv:2609.30342v1 Announce Type: cross Abstract: iKFAD is a recently proposed optimiser that replaces adaptive learning rates with adaptive friction in the momentum dynamics, yet performs as well as
arXiv:2609.30495v1 Announce Type: new Abstract: Autonomous navigation in previously unseen environments requires effective perception, persistent environmental representation, and collision avoidance
arXiv:2609.31325v1 Announce Type: new Abstract: Continual spatio-temporal forecasting supports traffic management and environmental monitoring under evolving dynamics and expanding sensor networks. Ho
arXiv:2609.30795v1 Announce Type: new Abstract: Existing human motion diffusion methods provide strong motion generation quality, and recent style transfer models can inject target style cues, but fin
arXiv:2609.30296v1 Announce Type: new Abstract: Neural networks are becoming popular in solving mathematical problems, but stochastic models do not provide mathematical exactness by themselves. This s
arXiv:2609.31078v1 Announce Type: new Abstract: Debates amongst agents driven by large language models (LLMs) have demonstrated vast potential in various applications, but when these interactions incl
arXiv:2609.30749v1 Announce Type: new Abstract: Data Science Code Translation (DSCT) is the process of converting code between data science libraries while preserving functional equivalence and enabli
arXiv:2609.30337v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates knowledge obsolescence and factual hallucination in large language models by introducing external context
arXiv:2609.30989v1 Announce Type: new Abstract: Purpose: Accurate 6 DoF pose estimation of surgical tools is critical for automa- tion, robotic proprioception, and safe interaction with the tissue ope
arXiv:2609.30684v1 Announce Type: new Abstract: Brazil's Pix settles about 5.9 billion instant, irreversible transfers a month. A fraudulent transfer can be recovered only while the funds remain in a
arXiv:2609.30735v1 Announce Type: new Abstract: Mobile humanoid manipulation requires both reaching a usable workspace and preserving precise hand-object interactions as object poses and contact condi
arXiv:2609.30554v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated promising capabilities as in-context policy optimizers for Reinforcement Learning (RL), enabling
arXiv:2609.30558v1 Announce Type: cross Abstract: Agent memory systems are increasingly used to maintain long-term user preferences, task states and evolving facts, but current evaluations often colla
arXiv:2609.31351v1 Announce Type: new Abstract: Time-series carry structure simultaneously at multiple scales (fine-grained variation, mid-range motifs, and global properties) and downstream tasks ope
arXiv:2606.06393v2 Announce Type: replace Abstract: Proper scoring rules provide a rigorous theoretical basis for the training and evaluation of probabilistic forecasts. In survival analysis, such for
arXiv:2510.05191v3 Announce Type: replace-cross Abstract: Conditional generation and disentangled representation learning are central to controlled generation across audio, vision, and multimodal doma
arXiv:2609.31028v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot (ZS) classification on histology images but do not perform as well on cytology, whose stains and
arXiv:2609.31337v1 Announce Type: new Abstract: Building a robotic manipulation system requires connecting perception, planning, and control through carefully designed representations and interfaces.
arXiv:2609.31518v1 Announce Type: cross Abstract: Sintering is widely used to manufacture ceramics, but coupled densification and grain growth, material-dependent kinetics, and sparse measurements com
arXiv:2609.31016v1 Announce Type: new Abstract: Generalization in Reinforcement Learning (RL) refers to the ability to execute close-to-optimal policies in unseen tasks after the agent has been traine
arXiv:2609.31466v1 Announce Type: new Abstract: Graph neural networks (GNNs) rely on message passing over graph edges, making their computational and memory costs strongly dependent on graph density.
arXiv:2609.30971v1 Announce Type: new Abstract: Embodied agents offer a promising route to automating scientific experimentation, yet their progress is constrained by the lack of reliable and systemat
arXiv:2609.30861v1 Announce Type: new Abstract: Language-model agents increasingly improve by converting execution experience into reusable external skills. Yet repeated skill updates form a learning
arXiv:2609.30294v1 Announce Type: cross Abstract: Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clea
arXiv:2609.30941v1 Announce Type: cross Abstract: Single-image novel view synthesis (NVS) enables photorealistic rendering of un- observed viewpoints from a single input. Practical NVS systems require
arXiv:2509.26473v2 Announce Type: replace Abstract: Unified Multimodal Understanding and Generation Models (UMMs) increasingly combine visual understanding and image generation within a single interac
arXiv:2605.05236v2 Announce Type: replace-cross Abstract: In the field of precision manufacturing in complex constrained environments, the role of soft robots is increasingly prominent, and the realiz