Knowledge catalogue
2026: the year of explosive AI innovation. @FireworksAI_HQ Co-founder & CEO Lin Qiao speaks on how the massive expansion of customized inference and models is creating speed of light production to sca
arXiv:2604.23045v1 Announce Type: new Abstract: Systematic biases in Global Circulation Model (GCM) outputs limit their direct applicability in regional planning, necessitating bias correction. Correc
arXiv:2604.23271v1 Announce Type: new Abstract: Automated white blood cell (WBC) classification is essential for scalable leukaemia screening. However, real-world deployment is challenged by domain sh
arXiv:2604.23239v1 Announce Type: new Abstract: Accurate long-term time series forecasting (LTSF) requires the capture of complex long-range dependencies and dynamic periodic patterns. Recent advances
arXiv:2604.23251v1 Announce Type: cross Abstract: Code review is central to software engineering education but hard to scale in capstone projects due to tight deadlines, uneven peer feedback, and limi
arXiv:2604.23418v1 Announce Type: new Abstract: Uniform random rotations are a useful primitive in applications such as fast Johnson-Lindenstrauss embeddings, kernel approximation, communication-effic
arXiv:2601.22925v2 Announce Type: replace-cross Abstract: Recent years have seen a rapid surge in research leveraging Large Language Models (LLMs) for recommendation. These methods typically employ su
arXiv:2604.22781v1 Announce Type: cross Abstract: Proactive alert prediction in computer networks is critical for mitigating evolving cyber threats and enabling timely defensive actions. Temporal Grap
arXiv:2604.24136v1 Announce Type: new Abstract: Pretrained diffusion models have revolutionized real-world image super-resolution (Real-ISR) but suffer from computational bottlenecks due to iterative
arXiv:2602.17513v2 Announce Type: replace Abstract: Clinical free-text notes contain vital patient information. They are structured into labelled sections; recognizing these sections has been shown to
arXiv:2303.05330v1 Announce Type: cross Abstract: Geo-distributed ML training can benefit many emerging ML scenarios (e.g., large model training, federated learning) with multi-regional cloud resource
The rise of vibe coding is pushing software teams to build faster than ever before, but enterprise buyers demand systems that can survive audits and operational risk. The result is a new kind of softw
arXiv:2604.23003v1 Announce Type: new Abstract: In this paper, we propose a Physics-Informed Neural Network framework for time-dependent simulations of pollution propagation originating from moving em
ComfyStudio is open. We're launching a physical R&D studio and artist residency program in LA this May pairing working VFX artists, animators, and pipeline folks with the ComfyUI team to build hybrid
arXiv:2604.24648v1 Announce Type: new Abstract: Climate change and resource depletion demand a shift from the dominant linear 'take-make-use-dispose' paradigm of construction toward circular, low-wast
arXiv:2604.23563v1 Announce Type: cross Abstract: Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disr
arXiv:2511.23036v2 Announce Type: replace-cross Abstract: Explaining online time series monitoring models is crucial across sensitive domains such as healthcare and finance, where temporal and context
arXiv:2406.10185v2 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging r
arXiv:2604.23570v1 Announce Type: new Abstract: The advancement of robot learning is currently hindered by the scarcity of large-scale, high-quality datasets. While established data collection methods
arXiv:2604.24041v1 Announce Type: cross Abstract: Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from down
arXiv:2604.23033v1 Announce Type: new Abstract: Radar-Inertial Odometry (RIO) based on the Extended Kalman Filter (EKF) relies on accurate extrinsic calibration between the radar and the Inertial Meas
arXiv:2512.07371v3 Announce Type: replace-cross Abstract: Behavior-cloning based visuomotor policies enable precise manipulation but often inherit the slow, cautious tempo of human demonstrations, lim
arXiv:2604.23730v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capaci
arXiv:2506.23210v5 Announce Type: replace-cross Abstract: Federated learning (FL) enables collaborative model training across distributed clients while preserving data privacy. However, data and syste
arXiv:2604.24590v1 Announce Type: new Abstract: Technological advancements in cryptocurrency markets have increased accessibility for investors, but concurrently exposed them to the risks of market ma
arXiv:2604.22792v1 Announce Type: cross Abstract: Conventional microwave engineering education relies heavily on analytical methods, canonical circuit topologies, and intuition-driven design, which ha
arXiv:2604.23474v1 Announce Type: new Abstract: Forecasting systems in science must be accurate, physically consistent, and certifiably reliable. Most existing models address prediction, constraint en
arXiv:2604.23779v1 Announce Type: cross Abstract: The semantic gap between colloquial user queries and professional legal documents presents a fundamental challenge in Legal Case Retrieval (LCR). Exis
arXiv:2511.09749v2 Announce Type: replace Abstract: Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris f
arXiv:2603.17573v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) Models have become the mainstream solution for robot control, but suffer from slow inference speeds. Speculative
arXiv:2604.23573v1 Announce Type: cross Abstract: Semi-supervised classification, where unlabeled data are massive but labeled data are limited, often arises in machine learning applications. We addre
arXiv:2604.23295v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems can model natural conversational behaviours such as interruptions, overlaps, and backchannels, yet such systems re
Harrison Chase announced plans to create multiple deepagents examples using the deepagent deploy tool and solicited community input on which examples would be most valuable. This post likely seeks fee
arXiv:2604.23059v1 Announce Type: new Abstract: Clinical framing -- the linguistic manner in which clinical information is presented -- can influence patient understanding and decision-making, with im
Manufacturing is shifting from relying solely on real-world testing, as high-fidelity simulation now produces synthetic training data accurate enough for production-grade AI. NVIDIA Omniverse librarie
arXiv:2604.22857v1 Announce Type: new Abstract: This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional ne
This post likely discusses how AI systems, particularly language models, can implicitly agree to tasks or commitments during conversations without formally recording or tracking these obligations, whi
arXiv:2604.24293v1 Announce Type: cross Abstract: Graph neural ordinary differential equations (Graph ODEs) extend graph learning from discrete message-passing layers to continuous-time representation
arXiv:2511.21213v2 Announce Type: replace-cross Abstract: Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, ZT. To accelerate the dis
arXiv:2604.23683v1 Announce Type: new Abstract: Historical encrypted manuscripts require both paleographic interpretation of cipher symbols and cryptanalytic recovery of plaintext. Most existing compu
arXiv:2604.24717v1 Announce Type: new Abstract: Every Transformer architecture dedicates enormous capacity to learning rich representations in semantic embedding space -- yet the rotation manifold act
arXiv:2604.23809v1 Announce Type: new Abstract: Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity s
arXiv:2512.10551v2 Announce Type: replace-cross Abstract: The commercialization of LLM applications is the next frontier in online advertising, with LLM-native advertising emerging as a promising para
arXiv:2604.24182v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models predominantly rely on end-to-end fine-tuning. While effective, this paradigm compromises the inherent genera
arXiv:2604.24143v1 Announce Type: new Abstract: Accurate modeling of outdoor-to-indoor (O2I) and indoor-to-indoor (I2I) signal loss is important for improving indoor wireless network performance in de
arXiv:2604.22828v1 Announce Type: cross Abstract: Recent generative AI models have achieved remarkable breakthroughs in language and visual understanding. However, although these models can generate r
arXiv:2604.23289v1 Announce Type: cross Abstract: Due to the unprecedented success of deep learning, it has become an integral component in several multimedia computing applications in todays world. U
Aditya Soni / Reuters: Microsoft is rolling out Copilot 365 to all of Accenture's roughly 743,000 employees, in the biggest enterprise deal for Copilot, following a 2023 pilot — Microsoft (MSFT.O) is
This post criticizes Microsoft's approach to integrating AI assistants into Outlook, expressing frustration that the AI chatbot has limited functionality and capabilities despite Microsoft's ownership
arXiv:2604.23108v1 Announce Type: cross Abstract: Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficient
arXiv:2604.23053v1 Announce Type: new Abstract: Mixed Binary Quadratic Programs (MBQPs) are an important and complex set of problems in combinatorial optimization. As solving large-scale combinatorial
arXiv:2604.23107v1 Announce Type: cross Abstract: Causal effect estimation from observational data requires careful adjustment for confounding. Classical estimators such as inverse probability weighti
arXiv:2604.23272v1 Announce Type: new Abstract: Humans understand and interact with the real world by relying on diverse physical feedback beyond visual perception. Motivated by this, recent approache
arXiv:2408.08686v4 Announce Type: replace-cross Abstract: Language Models (LMs) have been widely used in recommender systems to incorporate textual information of items into item IDs, leveraging their
arXiv:2405.16730v2 Announce Type: replace-cross Abstract: Noise Contrastive Estimation (NCE) has fueled major breakthroughs in representation learning and generative modeling. Yet a long-standing chal
arXiv:2604.23837v1 Announce Type: new Abstract: Large language models are increasingly deployed as advisors in high-stakes domains -- answering medical questions, interpreting legal documents, recomme
arXiv:2604.24125v1 Announce Type: new Abstract: Semantic segmentation of multi-modal remote sensing imagery plays a pivotal role in land use/land cover (LULC) mapping, environmental monitoring, and pr
arXiv:2604.24167v1 Announce Type: new Abstract: Implicit neural representations (INRs) are increasingly being used as tools to map coordinates to signals, encompassing applications from neural fields
arXiv:2604.23600v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in persona-driven applications such as education, customer service, and social platforms, where m
arXiv:2604.22758v1 Announce Type: cross Abstract: Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. T