Knowledge catalogue
arXiv:2505.18190v5 Announce Type: replace-cross Abstract: Physics sensing plays a central role in many scientific and engineering domains, which inherently involves two coupled tasks: reconstructing d
arXiv:2602.07518v2 Announce Type: replace-cross Abstract: Kolmogorov-Arnold Networks (KANs) shift neural computation from linear layers to learnable nonlinear edge functions, but implementing these no
arXiv:2605.23971v1 Announce Type: cross Abstract: This work presents a physics-guided machine-learning framework for carbon monoxide concentration inference from experimentally measured resistance tra
arXiv:2601.10012v2 Announce Type: replace Abstract: Multimodal decentralized federated learning (DFL) must support collaboration among agents that hold different modality subsets and often different m
arXiv:2605.24570v1 Announce Type: cross Abstract: Despite the central role of optimization in deep learning, most optimizers rely on update structures whose functional form is fixed before training be
arXiv:2601.13236v2 Announce Type: replace-cross Abstract: Parallel imaging techniques reduce magnetic resonance imaging (MRI) scan time but image quality degrades as the acceleration factor increases.
arXiv:2601.05613v2 Announce Type: replace-cross Abstract: While collaborative forecasting on distributed time series is highly desirable, directly pooling localized datasets is often impractical due t
arXiv:2605.24421v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as analyst assistants in security operations centers (SOCs), where they ingest log and alert data t
arXiv:2605.25958v1 Announce Type: new Abstract: This paper introduces PolyGnosis 2.0, a pioneering multi-agent architecture designed to extract predictive intelligence by synthesizing Polymarket anoma
arXiv:2605.24465v1 Announce Type: new Abstract: Robots benefit from sensory information to coordinate body movement, gain robustness against perturbations, and transit between different modes to adapt
arXiv:2605.24577v1 Announce Type: cross Abstract: Independently trained transformers compute the same function in residual-stream bases that differ by a uniform random rotation on SO(d_{model}). We ca
arXiv:2605.25085v1 Announce Type: cross Abstract: We study the rate-distortion limits of online KV cache compression in autoregressive language models, formulating it as sequential Wyner-Ziv source co
arXiv:2602.01322v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) interpret neural network representations by decomposing activations into sparse combinations of dictionary atoms. H
arXiv:2605.24622v1 Announce Type: new Abstract: A robot resolving ``put the cup on that one'' must fuse gesture, language, and scene geometry, yet 3D grounding benchmarks only partially capture this r
arXiv:2605.24558v1 Announce Type: new Abstract: AI for Science (AI4Science) workflows often treat the released dataset as a fixed interface to the underlying system. However, in domains relying on ind
arXiv:2605.25271v1 Announce Type: cross Abstract: We study the symmetric polynomial prod_{alphain A_{n,d}}igl(1+alpha_1 x_1+dots+alpha_n x_nigr) where A_{n,d}:={alphainZ_{ge 0}^n:|alpha|=d}, which is
arXiv:2605.25664v1 Announce Type: cross Abstract: Poor posture is a significant concern due to its detrimental effects on health and productivity. This paper presents a collar-clipped device called Po
arXiv:2603.18363v2 Announce Type: replace-cross Abstract: Unsupervised Reinforcement Learning from Internal Feedback (RLIF) has emerged as a promising paradigm for eliciting the latent capabilities of
arXiv:2605.25704v1 Announce Type: new Abstract: In contemporary large language models (LLMs), the swish-gated linear unit (SwiGLU) activation function is widely adopted to regulate the information flo
arXiv:2605.25127v1 Announce Type: cross Abstract: Point clouds are a fundamental 3D representation in computer vision, enabling a wide range of perception tasks. However, real-world point clouds often
arXiv:2605.23934v1 Announce Type: new Abstract: Quantum computing devices are recognized as powerful tools for solving NP-complete problems. However, the intricacy of their modeling presents notable b
arXiv:2502.15835v5 Announce Type: replace-cross Abstract: Pragmatic reasoning helps interlocutors infer intended meaning from ambiguous or underspecified messages by considering shared context and cou
arXiv:2605.25894v1 Announce Type: new Abstract: Predicting stock price movements during Earnings Announcements (EAs) is a significant challenge due to market noise and high-impact price discontinuitie
arXiv:2605.13643v2 Announce Type: replace Abstract: On-policy distillation (OPD) trains a student model on its own rollouts using dense feedback from a stronger teacher. Prior literature suggests that
arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov
arXiv:2605.25362v1 Announce Type: new Abstract: The strong dynamic coupling between the manipulator and the base poses a significant challenge to maintaining spacecraft attitude stability, potentially
arXiv:2605.26110v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) achieve versatility by reformulating diverse tasks into a unified instruction-following framework via instruc
arXiv:2602.08426v2 Announce Type: replace-cross Abstract: Block-sparse attention is promising for accelerating long-context LLM pre-filling, yet identifying relevant blocks efficiently remains a bottl
arXiv:2605.25020v1 Announce Type: new Abstract: Chronic dermatologic diseases such as pemphigus require long-term follow-up, generating extensive longitudinal clinical documentation that is difficult
arXiv:2605.24295v1 Announce Type: new Abstract: We propose PACE-GGM, a data-adaptive differentially private method for covariance estimation that concentrates its privacy budget on the most informativ
arXiv:2605.24249v1 Announce Type: new Abstract: The growing availability of clinical data has increased the use of machine learning, yet centralized data aggregation is often infeasible for sensitive
arXiv:2605.25404v1 Announce Type: new Abstract: Cascaded Automatic Speech Recognition -- Large Language Model (ASR-LLM) pipelines remain popular for industrial Spoken Dialogue Systems (SDS), primarily
arXiv:2605.24900v1 Announce Type: new Abstract: Proactive task-oriented agents must autonomously anticipate user needs, identify actionable opportunities, and trigger software actions at appropriate m
arXiv:2510.27118v4 Announce Type: replace Abstract: Most expressivity results for transformers treat them as language recognizers -- devices that accept or reject strings -- rather than as they are us
arXiv:2509.07961v2 Announce Type: replace Abstract: We develop new experimental paradigms for measuring welfare in language models. We compare verbal reports of models about their preferences with pre
arXiv:2605.25682v1 Announce Type: cross Abstract: Distributing Transformer inference across embedded edge devices can alleviate individual memory and compute constraints, yet practical benefits on rea
arXiv:2603.20479v2 Announce Type: replace-cross Abstract: Learning another language can be a highly emotional process, typically characterized by numerous frustrations and triumphs, big and small. For
arXiv:2605.24171v1 Announce Type: cross Abstract: Large language models are increasingly used for vulnerability detection, yet their reliability under different prompt formulations remains uncharacter
arXiv:2605.24756v1 Announce Type: new Abstract: Language-model agents increasingly emit uncertainty signals throughout a trajectory, but existing agentic UQ evaluations often conflate ranking usefulne
arXiv:2507.05890v4 Announce Type: replace-cross Abstract: As psychometric surveys are increasingly used to assess the traits of large language models (LLMs), the need for scalable survey item generati
arXiv:2601.06870v2 Announce Type: replace-cross Abstract: Multimodal large language models have demonstrated strong ability in capturing semantic representations for multimodal sentiment analysis. The
arXiv:2605.25066v1 Announce Type: cross Abstract: Quantum machine learning (QML) is moving from research prototypes to deployed cloud services. As QML enters regulated industries, the integrity of the
arXiv:2605.23991v1 Announce Type: cross Abstract: There is a growing urgency to track greenhouse gasses with the resolution, precision and accuracy needed to support independent verification of CO_2 f
arXiv:2605.25252v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training language models, but in practice, verifiers are
arXiv:2605.24904v1 Announce Type: new Abstract: Machine-translated benchmarks are widely used to assess the multilingual capabilities of large language models (LLMs), yet translation errors in these b
arXiv:2605.25933v1 Announce Type: cross Abstract: Posttraumatic stress disorder (PTSD) is a prevalent and debilitating mental health condition with significant personal and societal impacts. Current c
arXiv:2605.23930v1 Announce Type: new Abstract: We introduce Quantum Frog, a two-player cooperative game built on a novel quantized-time mechanic in which the environment advances only when a player a
arXiv:2605.24920v1 Announce Type: cross Abstract: Quaternion neural networks are parameter-efficient and model multidimensional dependencies by representing four related features as a single entity. H
arXiv:2410.10652v4 Announce Type: replace-cross Abstract: Cells in multicellular organisms coordinate to form structural and functional niches. With spatial transcriptomics (ST) enabling gene expressi
arXiv:2605.24218v1 Announce Type: new Abstract: Deep research agents extend the role of search engines from retrieving keyword-matched pages to synthesizing knowledge, fundamentally changing how human
arXiv:2605.25955v1 Announce Type: cross Abstract: Large language models (LLMs) face a dual challenge in creative capability evaluation: existing benchmarks (e.g., Story Cloze Test, HellaSwag) measure
arXiv:2605.23956v1 Announce Type: new Abstract: Compound AI systems that chain multiple LLM calls into directed computation graphs are now the dominant architecture for production AI. Although these a
arXiv:2507.14760v2 Announce Type: replace-cross Abstract: While deep learning offers tremendous promise for scientific and medical imaging, any failures and hallucinations (predictions that do not coi
arXiv:2605.25041v1 Announce Type: new Abstract: 4D radar is increasingly attractive for robotic mapping because it provides range, azimuth, elevation, and Doppler measurements while remaining robust i
arXiv:2605.25057v1 Announce Type: cross Abstract: Neural networks with randomly generated hidden weights (RaNNs) have been extensively studied, both as a standalone learning method and as an initializ
arXiv:2605.23912v1 Announce Type: cross Abstract: We present Raon-Speech, a top-performing 9B-parameter speech language model (SpeechLM) for English and Korean speech understanding, answering, and gen
arXiv:2604.00963v2 Announce Type: replace-cross Abstract: We show polylogarithmic mixing time bounds for the alternating-scan sampler for positively weighted restricted Boltzmann machines. This is don
arXiv:2605.23994v1 Announce Type: cross Abstract: Digital avatar watermarking presents unique challenges: avatars are routinely post-processed with background replacement, reframing, and format conver
arXiv:2603.11001v2 Announce Type: replace-cross Abstract: Human uplift studies, or studies that measure the effects of AI access on human performance via randomized controlled trials (RCT) or similar
arXiv:2605.25171v1 Announce Type: new Abstract: In most existing AI humor research, humor was treated as either 'present' or 'not present.' We explore the concept of humor as a social interaction with