Knowledge catalogue
arXiv:2608.21371v1 Announce Type: cross Abstract: Perimeter-gated single-photon avalanche diodes (pg-SPADs) are known for their dynamic dark noise modulation capabilities. They are reported to trade n
arXiv:2608.22634v1 Announce Type: cross Abstract: Current work on improving reliability in large language model (LLM)- generated answers has primarily leveraged Retrieval-Augmented Generation (RAG), k
arXiv:2608.23054v1 Announce Type: new Abstract: SIMON and SIMECK belong to a family of Lightweight Cryptographic Algorithms (LCAs) based on the Feistel block cipher, designed for Internet of Things (I
arXiv:2608.21601v1 Announce Type: new Abstract: Benchmarks for scientific artificial intelligence are mostly written to be scored: multiple-choice questions, curated agent tasks with reference solutio
arXiv:2608.22773v1 Announce Type: new Abstract: Dynamic 3D Gaussian Splatting (3DGS) achieves photorealistic reconstruction of time-varying scenes, and recent physics-aware extensions improve extrapol
arXiv:2608.22284v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in re
arXiv:2608.22142v1 Announce Type: new Abstract: This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented
arXiv:2505.14240v3 Announce Type: replace Abstract: Integrating combinatorial optimization layers into neural networks has recently attracted significant research interest. However, many existing appr
arXiv:2509.20067v5 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in supporting medical diagnosis, with prompting-based methods offering a flexible and deployable mea
arXiv:2608.22833v1 Announce Type: cross Abstract: Large language models (LLMs) and vision-language models (VLMs) are expanding the range of behaviors that can be represented in agent-based simulations
arXiv:2608.23140v1 Announce Type: new Abstract: Achieving 360{eg} coverage is critical for the visual perception systems of autonomous vehicles. Fisheye cameras offer a cost-effective solution by enab
arXiv:2608.23035v1 Announce Type: new Abstract: As on-device LLM agents evolve into personal copilots, the mobile operating system has become a key testbed for this paradigm, making rigorous capabilit
arXiv:2608.22782v1 Announce Type: cross Abstract: The Solar wind is a continuous flow of charged particles emanating from the solar surface and governed by complex, interacting magnetohydrodynamic pro
arXiv:2608.22643v1 Announce Type: cross Abstract: Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches
Protecting capital in today's markets requires immense speed and precision. A financial analyst preparing a deal memo works across licensed market data, internal models, and confidential client files.
arXiv:2608.22314v1 Announce Type: new Abstract: Many image processing methods such as corner detection, optical flow and iterative enhancement make use of image tensors. Generally, these tensors are e
arXiv:2511.12484v2 Announce Type: replace-cross Abstract: With the integration of massive distributed energy resources and the widespread participation of novel market entities, the operation of activ
arXiv:2601.09716v2 Announce Type: replace Abstract: Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepre
arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr
arXiv:2608.23480v1 Announce Type: cross Abstract: Timely risk classification is essential in many clinical monitoring settings, where decisions must balance the benefit of classifying patients early f
arXiv:2412.07264v2 Announce Type: replace-cross Abstract: Understanding complex animal behaviors hinges on deciphering the neural activity patterns within brain circuits, making the ability to forecas
arXiv:2608.21597v1 Announce Type: cross Abstract: Clinical data sources such as electronic health records and wearable sensors record patient status repeatedly over follow-up, often at irregular times
arXiv:2608.22432v1 Announce Type: cross Abstract: Multilingual LLM judges produce different evaluator-backbone rankings depending on the prompt language: on an eight-language Agent-as-a-Judge benchmar
arXiv:2608.21626v1 Announce Type: new Abstract: Semantic communication shifts the objective of communication systems from accurate symbol reconstruction toward meaning preservation, task accomplishmen
arXiv:2608.21379v1 Announce Type: new Abstract: Student burnout is highly prevalent in higher education, with reported rates ranging from 12% to over 70% and consistently exceeding those of the workin
arXiv:2501.04001v4 Announce Type: replace Abstract: This work presents Sa2VA, the first comprehensive, unified model for dense grounded understanding of both images and videos. Unlike existing multi-m
arXiv:2608.22898v1 Announce Type: new Abstract: Diffusion language models (DLMs) alleviate the inherent latency bottleneck of autoregressive (AR) large language models (LLMs), but their degraded gener
arXiv:2608.22090v1 Announce Type: cross Abstract: Large language models can produce fluent reasoning traces whose local semantic errors propagate to an incorrect conclusion, while unconstrained self-c
arXiv:2608.23382v1 Announce Type: new Abstract: Instance encoding is a popular empirical technique for privacy enhancement when sharing data to an untrusted server. It transforms sensitive data throug
I’ve been experimenting with a custom inference/runtime research project called CRANE V2, mostly because I wanted to answer a stupid question: How far can you push absurdly large MoE models on an ordi
arXiv:2608.22086v1 Announce Type: cross Abstract: We present SweepLSD, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the
arXiv:2608.21409v1 Announce Type: cross Abstract: In medicine, claims remain valid when supported by empirical evidence grounded in stable biological reality. In law, by contrast, truth is contingent,
arXiv:2608.22622v1 Announce Type: cross Abstract: Clinical decision-making relies on identifying relevant patient information to guide diagnosis and treatment, a challenge that is especially difficult
arXiv:2511.02208v2 Announce Type: replace Abstract: Despite rapid progress, current AI agents are primarily optimized for isolated task completion. We argue for a paradigm shift toward training agents
arXiv:2602.18492v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are now good enough at coding that developers can describe intent in plain language and let the tool produce the
arXiv:2608.21445v1 Announce Type: new Abstract: Automated seizure detection from electroencephalography (EEG) is essential for continuous neurological monitoring, particularly for subclinical epilepti
arXiv:2608.23161v1 Announce Type: new Abstract: Heavy-duty vehicle diagnostics generate three disconnected data modalities: unstructured multi- lingual service complaints, high-dimensional sensor tele
arXiv:2608.22339v1 Announce Type: new Abstract: Extracting skills from past successes is critical for the efficient evolution of Large Language Model (LLM) agents. Prevailing agent self-evolution para
arXiv:2602.13739v2 Announce Type: replace Abstract: Mobile robotic gas distribution mapping (GDM) provides critical situational awareness during emergency responses to hazardous gas releases. However,
arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods
arXiv:2512.13530v2 Announce Type: replace-cross Abstract: Contour location---the process of sequentially training a surrogate model to identify the design inputs that result in a pre-specified respons
arXiv:2608.20481v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is an open source JSON-RPC protocol that standardizes how large language models (LLMs) interact with external systems
AgentX 1.0 is the first fully open‑source multi‑turn agentic coding inference benchmark (Apache 2.0), released August 2026 with a 1 million‑token context and over 1 million tokens of dataset built at
arXiv:2608.21187v1 Announce Type: cross Abstract: Pairwise reciprocal matrices are fundamental to the Analytic Hierarchy Process (AHP), a decision-making model. While the Direct Least Squares (DLS) me
arXiv:2510.16211v2 Announce Type: replace Abstract: Label noise is a common problem in real-world datasets, affecting both model training and validation. Clean data are essential for achieving strong
Share what your favorite models are right now and why. Given the nature of the beast in evaluating VLMs (untrustworthiness of benchmarks, immature tooling, intrinsic stochasticity), please be as detai
arXiv:2511.08142v2 Announce Type: replace Abstract: Federated Learning (FL) is a promising machine learning solution in large-scale IoT systems, guaranteeing load distribution and privacy. However, FL
Standard constrained RL assumes consequences are immediate and attributable to the current action. This breaks down whenever violations are delayed and stochastic, which is most real-world settings yo
arXiv:2608.20381v1 Announce Type: cross Abstract: Automating slide editing requires simultaneously satisfying modification accuracy, preservation fidelity, and robustness to deck length. Existing LLM-
arXiv:2310.12032v4 Announce Type: replace Abstract: The Linear Model of Co-regionalization (LMC) is a very general multitask gaussian process model for regression or classification. While its expressi
arXiv:2411.16478v3 Announce Type: replace Abstract: Measuring distribution drifts is a key task in managing distributed, sensitive data, as it underpins a wide range of federated learning and analytic
arXiv:2608.21156v1 Announce Type: cross Abstract: LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms includin
arXiv:2608.20350v1 Announce Type: cross Abstract: Traditional industrial agents rely on modular pipelines, including Router, Retriever, Planner, Executor, Responder, Reviewer, and other components. Th
arXiv:2608.20391v1 Announce Type: new Abstract: Most legal NLP resources draw from federal case law and focus on coarse classification, leaving administrative adjudication, where the vast majority of
arXiv:2608.20384v1 Announce Type: new Abstract: Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and
arXiv:2608.20743v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by allowing a lightweight drafter to propose future tokens while a target model verifies them
arXiv:2512.03262v3 Announce Type: replace-cross Abstract: Vibe coding is a new software development paradigm in which human engineers prompt a large language model (LLM) agent to complete complex codi
arXiv:2608.20938v1 Announce Type: new Abstract: Evaluators often produce correct labels via flawed reasoning, a critical failure for agentic systems gating actions, routing reviews, or supplying train
arXiv:2608.20626v1 Announce Type: cross Abstract: Soft, wearable robotic devices can deliver haptic feedback to support a wide range of tasks, such as extended reality, training various skills, and re
arXiv:2603.11252v2 Announce Type: replace Abstract: Although semantic 3D city models are internationally available and becoming increasingly detailed, the incorporation of material information remains