Knowledge catalogue
arXiv:2502.07295v2 Announce Type: replace Abstract: Neural Networks (NNs) for causal effect estimation have shown strong empirical performance, yet endowing them with desirable semiparametric properti
arXiv:2602.08404v2 Announce Type: replace Abstract: Diffusion large language models (dLLMs) have recently gained significant attention due to their inherent support for parallel decoding. Building on
arXiv:2605.23872v1 Announce Type: new Abstract: We introduce training-free looped transformers, in which a lightweight inference-time wrapper loops a contiguous mid-stack block of layers of a frozen c
arXiv:2603.01655v2 Announce Type: replace Abstract: Ray tracing has become a standard for accurate radio propagation modeling, but suffers from exponential computational complexity, as the number of c
arXiv:2605.23171v1 Announce Type: cross Abstract: Recent advancements in instructional fine-tuning have injected noise into embeddings, with NEFTune (Jain et al., 2024) setting benchmarks using unifor
arXiv:2511.00266v2 Announce Type: replace Abstract: Accurate trajectory prediction is crucial for safe and reliable autonomous driving systems, requiring models that capture long-term temporal depende
Q: How are job postings for software engineers rising rapidly despite AI agents automating coding? A: Because there’s far more code to manage than ever before. We’re already seeing a 14x YoY increase
arXiv:2601.21025v3 Announce Type: replace-cross Abstract: Score-based generative models have recently achieved remarkable success. While they are usually parameterized by the score, an alternative way
arXiv:2411.08126v2 Announce Type: replace-cross Abstract: We study offline dynamic pricing when historical data provide incomplete coverage of the price space such that some candidate prices, includin
arXiv:2605.22111v1 Announce Type: new Abstract: Accurate modeling of aerodynamic loads is essential for understanding and predicting the responses of complex structural systems. However, these models
arXiv:2605.21560v1 Announce Type: new Abstract: Deploying neural networks on microcontroller units (MCUs) is critical for edge intelligence but remains challenging due to tight memory, storage, and co
arXiv:2510.10129v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems suffer from severe time-to-first-token (TTFT) bottlenecks due to long input sequences. Existing KV cach
arXiv:2605.21846v1 Announce Type: cross Abstract: Causal discovery from multivariate time series is challenging when causal effects may occur both across time and within the same sampling interval. Th
arXiv:2605.21499v1 Announce Type: cross Abstract: Grid-based neural networks such as convolutional autoencoders are widely used in dimension reduction-based surrogate models for computational fluid dy
arXiv:2509.08933v2 Announce Type: replace Abstract: We study the problem of learning the optimal policy in a discounted, infinite-horizon reinforcement learning (RL) setting in the presence of adversa
arXiv:2605.21903v1 Announce Type: cross Abstract: The integration of machine learning with domain-specific physics is transforming the design, monitoring, and control of electricity systems, where dat
arXiv:2605.22304v1 Announce Type: cross Abstract: Integrating new data into knowledge graphs (KG) typically involves different tasks that are executed within workflows or pipelines There are many poss
arXiv:2605.22243v1 Announce Type: new Abstract: Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to desi
arXiv:2602.03067v3 Announce Type: replace Abstract: Entropic optimal transport (EOT) via Sinkhorn iterations is widely used in modern machine learning, yet GPU solvers remain inefficient at scale. Ten
arXiv:2605.21731v1 Announce Type: new Abstract: Deep learning models are increasingly used in scientific prediction tasks where strong benchmark performance is often interpreted as evidence of scienti
arXiv:2605.22556v1 Announce Type: new Abstract: Digital elevation models (DEMs) underpin terrain analysis in Geographic Information Systems (GIS), but in their common raster form, they rely on interpo
arXiv:2601.05157v2 Announce Type: replace-cross Abstract: In this work, we give a {rm poly}(d,k) time and sample algorithm for efficiently learning the parameters of a mixture of k spherical distribut
arXiv:2601.21853v2 Announce Type: replace-cross Abstract: Multi-vector representations generated by late interaction models, such as ColBERT, enable superior retrieval quality compared to single-vecto
arXiv:2605.22717v1 Announce Type: cross Abstract: Interactive streaming music generation promises the use of generative models for live performance and co-creation that is impossible with offline mode
arXiv:2503.06115v2 Announce Type: replace-cross Abstract: Reinforced random walks (RRWs), including vertex-reinforced random walks (VRRWs) and edge-reinforced random walks (ERRWs), model random walks
arXiv:2605.21752v1 Announce Type: new Abstract: Recommender systems trained on user interaction data are susceptible to behavioral intensity imbalance--a systematic distortion arising from heterogeneo
This Databricks resource discusses how pharmaceutical companies can use analytics to optimize their product launch strategy, focusing on accelerating critical decision-making during the crucial first
arXiv:2602.22270v2 Announce Type: replace Abstract: Spatio-temporal epidemic forecasting is critical for public health management, yet existing methods often struggle with insensitivity to weak epidem
arXiv:2605.22463v1 Announce Type: cross Abstract: Scalable trapped-ion quantum computing is commonly realized with modular chips that feature distinct zones with specific functionalities, such as stor
arXiv:2605.21813v1 Announce Type: new Abstract: Discrete probability laws underpin statistical modeling, yet the catalog of interpretable distributions has expanded only gradually through centuries of
arXiv:2605.22740v1 Announce Type: new Abstract: Decision trees partition the feature space using hard binary thresholds, assigning identical confidence to instances far from a decision boundary and to
arXiv:2603.04525v2 Announce Type: replace-cross Abstract: Modern approaches for learning from non-Markovian time series, such as recurrent neural networks, neural controlled differential equations or
arXiv:2605.22366v1 Announce Type: new Abstract: Agricultural decision-making increasingly requires multimodal systems that can transform visual observations into reliable, executable actions. However,
arXiv:2605.22034v1 Announce Type: new Abstract: Visual grounding, the task of localizing objects described by natural-language expressions, is a foundational capability for agricultural AI systems, en
This article discusses three AI infrastructure startups—Exa, Modal, and TurboPuffer—that have recently achieved unicorn status (valued at $1 billion or more). The piece likely covers their funding rou
United Kingdom-based Blockchain.com Group Holdings Inc., a cryptocurrency exchange and wallet service, announced Thursday that it has filed confidentially for an initial public offering in the United
arXiv:2605.22605v1 Announce Type: cross Abstract: Object detection from Unmanned Aerial Vehicles (UAVs) is challenged by severe ego-motion, camera jitter, and large scale variations. While modern dete
arXiv:2605.22420v1 Announce Type: new Abstract: Urban scene reconstruction from real-world observations has emerged as a powerful tool for self-driving development and testing. While current neural re
arXiv:2509.09215v2 Announce Type: replace Abstract: Large language models (LLMs)-empowered autonomous agents are transforming both digital and physical environments by enabling adaptive, multi-agent c
arXiv:2605.22185v1 Announce Type: new Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding. However, thei
arXiv:2503.17599v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated considerable potential in general practice. However, existing benchmarks and evaluation frameworks pr
arXiv:2605.22258v1 Announce Type: new Abstract: Large language models (LLMs) require robust toxicity evaluation beyond explicit wording. This setting remains underexplored in Chinese, where toxicity m
Harvard University just voted to limit the number of A grades given in undergraduate classes to about 20% of the class. I’m not in favor of this. It deeply runs counter to how I believe education shou
arXiv:2605.20704v1 Announce Type: cross Abstract: Autonomous AI agents that spawn sub-agent swarms create a safety gap: existing credential revocation mechanisms, OAuth~2.0 introspection, OCSP, and W3
This Reddit post discusses a common ComfyUI issue where users cannot locate spatial upscaler models for img2vid workflows. The problem typically stems from placing spatial upscaler models in the wrong
arXiv:2507.15777v3 Announce Type: replace Abstract: Rich and accurate medical image segmentation is poised to underpin the next generation of AI-defined clinical practice by delineating critical anato
arXiv:2605.20520v1 Announce Type: new Abstract: Benchmark-based evaluation remains important for tracking frontier AI progress. But it can both overstate and understate deployed capability because it
arXiv:2605.22487v1 Announce Type: new Abstract: Recent advances in Multilingual Large Language Models (MLLMs) have significantly enhanced cross-lingual conversational capabilities, yet modeling cultur
arXiv:2605.22351v1 Announce Type: new Abstract: Low-bit quantization is widely used to compress super-resolution (SR) models and reduce storage and computation costs for deployment on resource-limited
arXiv:2509.23582v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) have recently emerged as a powerful backbone for image generation, demonstrating superior scalability and performance
arXiv:2506.14648v2 Announce Type: replace Abstract: Preference-based Reinforcement Learning (PbRL) methods provide a solution to avoid reward engineering by learning reward models based on human prefe
arXiv:2602.08064v2 Announce Type: replace-cross Abstract: The long-standing tension between Pre- and Post-Norm remains an open problem in Transformer architecture, reflecting a fundamental trade-off b
arXiv:2605.22748v1 Announce Type: new Abstract: Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, dynamic real-world spaces. This f
arXiv:2605.20742v1 Announce Type: new Abstract: With the rapid proliferation of electric vehicles, the safety and reliability of lithium-ion batteries have become critical concerns. Effective anomaly
DeepSeek has announced a permanent discount for its DeepSeek-V4-Pro model, encouraging developers to build and innovate with the platform. The announcement was made via social media and emphasizes the
Sam Altman posed a question to the public asking what problem they most hope AI will solve in the future, with an implied offer that OpenAI might be able to help address it. The post invites community
arXiv:2605.20494v1 Announce Type: new Abstract: Reliable assessment of tropical cyclone (TC) risk is limited by the brevity and spatial sparsity of the historical record, particularly for the rare, hi
arXiv:2605.21058v1 Announce Type: new Abstract: Causal representation learning (CRL) and traditional representation learning have largely developed along different trajectories. Traditional representa
arXiv:2410.03296v4 Announce Type: replace Abstract: Instruction-tuned LLMs are able to provide extit{an} explanation about their output to users by generating self-explanations, without requiring the
arXiv:2605.20220v1 Announce Type: cross Abstract: A musical score provides the essential instructions for its performance while containing indications - at times implicit - regarding the composer's in