Knowledge catalogue
arXiv:2608.04404v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot manipulation by learning how the environment evolves beyond the current observation. However, existing approach
arXiv:2608.04073v1 Announce Type: cross Abstract: Personalized Federated Learning (PFL) has emerged as a promising solution for intrusion detection in heterogeneous IoT environments, as it can improve
arXiv:2608.04242v1 Announce Type: new Abstract: Ubiquitous companion robots offer a promising avenue for immediate anxiety relief in children, yet their effectiveness relies on the ability to monitor
arXiv:2512.02567v2 Announce Type: replace-cross Abstract: The advent of strong generative AI has a considerable impact on various software engineering tasks such as code repair, test generation, or la
arXiv:2608.04771v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) excel on complex tasks through long chain-of-thought (CoT) reasoning, but their lengthy intermediate steps cause severe ov
arXiv:2608.04095v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used as personalized assistants in high-stakes domains such as financial advising, yet it remains unc
arXiv:2608.04077v1 Announce Type: new Abstract: Evaluating financial AI agents requires criteria aligned with real professional work. Existing rubric methods typically derive criteria from task prompt
arXiv:2608.04374v1 Announce Type: cross Abstract: Large language models can produce fluent financial analysis, but fluency alone does not establish whether a report is suitable for institutional deliv
arXiv:2511.07322v3 Announce Type: replace-cross Abstract: While LLMs have shown great success in financial tasks like stock prediction and question answering, their application in fully automating Equ
arXiv:2602.19161v2 Announce Type: replace Abstract: Latent diffusion models have enabled high-quality video synthesis, yet their inference remains costly and time-consuming. As diffusion transformers
arXiv:2608.04050v1 Announce Type: cross Abstract: Wi-Fi networks are moving beyond random channel access toward tightly coordinated operation across access points (APs), a shift reflected in Wi-Fi 8's
arXiv:2608.04530v1 Announce Type: new Abstract: GUI agents must remember both useful experience from earlier tasks and unfinished progress in the current interaction. Latent memory offers a compact so
arXiv:2608.04423v1 Announce Type: new Abstract: Fossil leaves are rarely preserved whole -- sedimentary rock hides, breaks, and erodes the lamina, yet paleobotany depends on the complete shape and out
arXiv:2603.00195v2 Announce Type: replace-cross Abstract: 32 pages, 5 theorems with full proofs, 68 references, open-source tool: https://github.com/qualixar/skillfortify. v2: corrects the bibliograph
arXiv:2608.04394v1 Announce Type: new Abstract: Cross-Domain Few-Shot Object Detection (CDFSOD) aims to transfer knowledge from data-rich upstream generic domains to downstream expert domains using sc
arXiv:2601.03808v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved notable performance in code synthesis; however, data-aware augmentation remains a limiting factor, handle
arXiv:2608.04200v1 Announce Type: cross Abstract: Financial sentiment classifiers are commonly evaluated against human labels, but strong linguistic performance does not necessarily imply economically
arXiv:2608.04206v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) often require high-accuracy quasi-Newton refinement to obtain reliable partial differential equation solutions,
arXiv:2608.05030v1 Announce Type: new Abstract: Football score forecasting combines a strong statistical core with a difficult contextual edge. Dynamic Poisson-family models estimate team strength, ex
arXiv:2608.04769v1 Announce Type: new Abstract: This paper presents an edge-aware instance segmentation framework that enables real-time robotic collision avoidance with transparent laboratory glasswa
arXiv:2604.01693v2 Announce Type: replace Abstract: Video object removal aims to erase target objects while reconstructing visually plausible and temporally coherent content. However, target objects o
arXiv:2512.19819v2 Announce Type: replace-cross Abstract: One of the primary applications of classical Boltzmann machines is generative modeling, wherein the goal is to tune the parameters of a model
arXiv:2608.04766v1 Announce Type: cross Abstract: A large number of infants with congenital anomalies are born each year globally, especially in areas with underdeveloped medical resources. Currently,
arXiv:2512.10222v2 Announce Type: replace-cross Abstract: Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physi
arXiv:2608.04612v1 Announce Type: new Abstract: We present GASP, a GPU-Accelerated Safe Planner for real-time, collision-aware joint-space motion generation in known environments. GASP combines a clam
arXiv:2507.04004v3 Announce Type: replace Abstract: This paper presents the first photo-realistic LiDAR-Inertial-Camera Gaussian Splatting SLAM system that simultaneously addresses visual quality, geo
arXiv:2608.04111v1 Announce Type: cross Abstract: Can a model look at a river delta and a lightning bolt and see that they share a structure? We introduce GEB-Bench, a benchmark whose unit is an abstr
arXiv:2507.03897v3 Announce Type: replace Abstract: We introduce GenAI-Powered Inference (GPI), a statistical framework for both causal and predictive inference using unstructured data, including text
arXiv:2508.12226v3 Announce Type: replace Abstract: Ultrasound Tomography (UT) is a radiation-free, high-resolution modality, but remains limited for musculoskeletal imaging due to the high computatio
arXiv:2608.04421v1 Announce Type: cross Abstract: Incentivized advertising allocates monetary or virtual rewards to drive user engagement, where a key challenge is optimizing continuous incentive magn
arXiv:2608.04257v1 Announce Type: new Abstract: Blood-brain barrier permeability (BBBP) prediction is a critical screening task in central nervous system drug discovery, where candidate molecules must
arXiv:2608.04504v1 Announce Type: cross Abstract: Vision-language models excel in many multimodal tasks but remain prone to a subtle yet impactful failure mode: they tend to overestimate dominant visu
arXiv:2608.05075v1 Announce Type: new Abstract: The spread of misinformation is widely perceived as a threat to democratic deliberation, yet how political elites' rhetorical commitments to truth shift
arXiv:2408.05885v3 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlo
arXiv:2608.04821v1 Announce Type: new Abstract: Image cropping aims to improve image aesthetics by preserving important content within an appropriately composed region. However, most existing methods
arXiv:2608.04018v1 Announce Type: cross Abstract: AI agents are increasingly embedded in organizational workflows, where they interact with external information sources and invoke digital tools to per
arXiv:2608.05045v1 Announce Type: cross Abstract: Released aligned large language models remain vulnerable to malicious downstream finetuning. Existing defenses are largely designed for the fine-tunin
arXiv:2503.06396v2 Announce Type: replace Abstract: The minimum vertex cover (MVC) problem seeks to identify the smallest set of vertices that cover all edges in an undirected graph. As a fundamental
arXiv:2510.26081v2 Announce Type: replace-cross Abstract: Near the critical point, Markov Chain Monte Carlo (MCMC) simulations of lattice quantum field theories (LQFT) become increasingly inefficient
arXiv:2608.04510v1 Announce Type: cross Abstract: Diffusion-based vision-language-action (VLA) policies can generate plausible actions even when their predictions are weakly grounded in the visual and
arXiv:2608.04772v1 Announce Type: cross Abstract: Scaling supervision for multi-turn medical agents is difficult because expert dialogue annotation is costly and clinical conversations are privacy-res
arXiv:2608.04240v1 Announce Type: cross Abstract: Superhuman game engines in domains like chess have made expert-level evaluations easily accessible, yet they communicate what is true without the natu
arXiv:2608.02009v2 Announce Type: replace Abstract: Retrieval-augmented search agents answer multi-hop questions by repeatedly issuing search queries and accumulating evidence. This creates a stopping
arXiv:2608.05063v1 Announce Type: cross Abstract: The semiconductor industry is undergoing a dual revolution: the shift toward heterogeneous 2.5D chiplet systems and the integration of Large Language
arXiv:2508.04811v2 Announce Type: replace Abstract: Order dispatch systems play a vital role in ride-hailing services, which directly influence operator revenue, driver profit, and passenger experienc
arXiv:2608.05070v1 Announce Type: new Abstract: Despite the remarkable recent progress of video world models, social interaction between users and the characters within these worlds remains unsupporte
arXiv:2608.04378v1 Announce Type: cross Abstract: Collaborative music agents need internal representations rich enough to support both understanding and generation, yet flexible enough for a workflow
arXiv:2608.05101v1 Announce Type: new Abstract: The emergence of medical deepfakes, i.e., medical images manipulated by deep generative models, poses a significant threat to clinical workflows. Howeve
arXiv:2608.05095v1 Announce Type: new Abstract: Agents for long term reasoning require a memory that can be efficiently and effectively updated over time, as new facts and external feedback continue t
arXiv:2608.04610v1 Announce Type: new Abstract: 3D vision-language models (3D VLMs) enable spatial reasoning over multi-view scenes but suffer from substantial token redundancy due to duplicated obser
arXiv:2606.17824v2 Announce Type: replace-cross Abstract: Segmenting 3D assets into meaningful regions remains challenging, especially when segmentation criteria are application-dependent and require
arXiv:2608.04351v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) excel at general speech understanding; however, adapting them to fine-grained tasks like Speech Emotion Recognitio
arXiv:2608.04379v1 Announce Type: cross Abstract: We propose a method to optimize the correlation among convolutional neural network (CNN) features that are used as inputs to quantum neural network (Q
arXiv:2608.04777v1 Announce Type: cross Abstract: Oscillatory signals, such as vibration, carry class-discriminative information in specific frequency bands; perturbing them in raw feature space for c
arXiv:2603.12408v3 Announce Type: replace-cross Abstract: Motion imitation learning (IL) is increasingly used in robotics and human gait modeling, yet its ability to recover biomechanically consistent
arXiv:2608.04384v1 Announce Type: new Abstract: Neural PDE solver auto-design is fundamentally a search-space representation problem. In the space of unrestricted Python programs, valid solvers form a
arXiv:2505.13099v3 Announce Type: replace Abstract: Vision Foundation Models (VFMs) have made remarkable progress and are increasingly being applied to segmentation tasks in real-world industrial sett
arXiv:2608.04761v1 Announce Type: cross Abstract: Self-improving agents accumulate reusable insights from prior trajectories, making retrieval increasingly important for turning accumulated experience
arXiv:2508.16440v2 Announce Type: replace-cross Abstract: Urban Air Mobility (UAM) envisions the widespread use of small aerial vehicles to transform transportation in dense urban environments. Howeve
arXiv:2608.04232v1 Announce Type: new Abstract: Biological systems must regulate competing needs under limited perceptual bandwidth, where sharpening one estimate costs the capacity to sharpen the oth