Knowledge catalogue
arXiv:2605.05092v1 Announce Type: cross Abstract: Safe L2/L3 driving automation requires anticipating human-in-the-loop reactions during shared-control transitions. While most driving world models for
arXiv:2601.19690v2 Announce Type: replace Abstract: Vision Mamba models have been extensively researched in various fields, which address the limitations of previous models by effectively managing lon
arXiv:2605.04997v1 Announce Type: new Abstract: DualTCN is the first deep-learning framework for inverting time-domain marine controlled-source electromagnetic (MCSEM) transient data. Moving away from
arXiv:2601.03166v2 Announce Type: replace Abstract: Choosing a suitable ML model is a complex task that can depend on several objectives, e.g., accuracy, fairness, or energy consumption. In practice,
arXiv:2509.14640v2 Announce Type: replace Abstract: Existing positional encoding methods in transformers are fundamentally signal-agnostic, deriving positional information solely from sequence indices
arXiv:2508.19145v3 Announce Type: replace-cross Abstract: Recurrent neural networks (RNNs) have become increasingly popular in information processing tasks involving time series and temporal data. A f
arXiv:2605.04062v1 Announce Type: new Abstract: Recent years have witnessed an increasing interest in deploying LLMs on resource-constrained devices, among which quantization has emerged as a promisin
arXiv:2503.03565v3 Announce Type: replace-cross Abstract: We analyze the efficiency of parallelization and restart mechanisms for stochastic simulations in model-free settings, where the underlying sy
arXiv:2605.04557v1 Announce Type: new Abstract: High-resolution satellite images are often scarce and costly, especially for remote areas or infrequent events. This shortage hampers the development an
arXiv:2605.04079v1 Announce Type: new Abstract: Early and reliable detection of Alzheimer's disease (AD) is crucial for timely clinical intervention and improved patient management. It also supports t
arXiv:2510.18518v2 Announce Type: replace Abstract: We present an online model-based reinforcement learning algorithm suitable for controlling complex robotic systems directly in the real world. Unlik
arXiv:2605.04356v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has been used to elicit impressive performance from language models in many domains. But, broadly benefic
arXiv:2605.04764v1 Announce Type: new Abstract: Large language models are increasingly used as surrogate models for low-data optimization, but their optimizer-facing prediction and its uncertainty rem
Elon Musk increased usage limits on a platform or service, likely referring to X (formerly Twitter) where he has made various policy adjustments since his acquisition. The specific limits doubled coul
Elon Musk / @elonmusk: Elon Musk says SpaceX reserves “the right to reclaim the compute” from Anthropic if its “AI engages in actions that harm humanity” — @MobofJoggers @nottombrown Just as SpaceX la
In 2018, Elon Musk wanted OpenAI founders Sam Altman, Greg Brockman, and Ilya Sutskever to lead Tesla's artificial intelligence projects. Musk proposed making OpenAI a Tesla subsidiary or hiring its t
Elon Musk’s DOGE “blatantly used” race, gender and other protected characteristics to execute the largest mass termination of federal grants in the history of the National Endowment for the Humanities
arXiv:2605.04709v1 Announce Type: new Abstract: A central challenge of visual control with model-based reinforcement learning (RL) is reliable long-horizon planning: long rollouts with learned latent
arXiv:2505.18244v3 Announce Type: replace Abstract: Why do language models from different architecture families respond so differently to the same perturbation? We argue that the answer is not scale,
arXiv:2605.04998v1 Announce Type: cross Abstract: Chord progression generation is practically important but understudied. Most large-scale symbolic music systems target melody, multi-track arrangement
arXiv:2605.04164v1 Announce Type: new Abstract: Wildfires are a major producer of fine particulate matter, impacting human health and the electrical grid. Accurately forecasting smoke impacts over lon
arXiv:2603.16368v2 Announce Type: replace-cross Abstract: Striking a balance between efficiency and transparent motion is a core challenge in human-robot collaboration, as highly expressive movements
arXiv:2605.04054v1 Announce Type: new Abstract: Achieving endogenous regime switching is crucial for the emergence of autonomous intelligence, yet remains a central challenge for existing machine lear
arXiv:2605.03242v1 Announce Type: new Abstract: Tool-using agent systems powered by large language models (LLMs) are increasingly deployed across web, app, operating-system, and transactional environm
arXiv:2605.04082v1 Announce Type: new Abstract: Model-based solutions for nitrous oxide (N2O) emissions from wastewater treatment plants (WWTP) are informed by operational datasets designed to control
arXiv:2605.04727v1 Announce Type: new Abstract: Programming Knowledge Tracing (PKT) has recently advanced through hybrid approaches that integrate attention-based feature modeling for code representat
Enterprise AI deployment has fundamentally expanded the cybersecurity attack surface, turning data pipelines, model training environments, identity management systems and supply chains into prime targ
arXiv:2605.04255v1 Announce Type: cross Abstract: Many machine learning problems involve data supported on curved spaces such as spheres, rotation groups, hyperbolic spaces, and general Riemannian man
EO-1 is now available directly in LeRobot! You can train, evaluate, and deploy EO-1 through the standard LeRobot policy interface, making it much easier to try EO-1 on robot-control workflows. Huge th
arXiv:2605.04960v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), particularly Group Relative Policy Optimization (GRPO), has advanced LLM reasoning. However, GRPO
Episode 3 of Max Agency is here! Join @hwchase17 + @Ramp’s Head of Applied Research Alex Shevchenko and go behind the scenes of Ramp Sheets. @RampLabs Talked to @ramplabs Head of Applied Research Alex
'¡Es cierto!' is a post from Nous Research shared on X (formerly Twitter). Without access to the specific URL content, this likely discusses verification of claims, confirmation of facts, or announcem
arXiv:2605.05179v1 Announce Type: new Abstract: By far the most common way to estimate an expected loss in machine learning is to draw samples, compute the loss on each one, and take the empirical ave
Pieter Haeck / Politico: EU legislators reach a deal to postpone restrictions on high-risk AI until December 2027 and to exempt the use of AI in industrial applications from the AI Act — Deal marks fi
arXiv:2605.04085v1 Announce Type: cross Abstract: Objectives: Large language models (LLMs) are increasingly used for clinical text summarization, yet structured methods to assess associated patient sa
arXiv:2605.03227v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning. However, their ability to perform ex
arXiv:2603.13824v2 Announce Type: replace-cross Abstract: Recent advances in text-to-audio generation enable models to translate natural-language descriptions into diverse musical output. However, the
arXiv:2605.04410v1 Announce Type: new Abstract: The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and
arXiv:2605.04548v1 Announce Type: new Abstract: Accurate early warning of vineyard disease risk from environmental observations is essential for timely intervention and more sustainable crop protectio
Every so often I think about how, in 2022, for $24B we could had 'prototype vaccines ready for each of the 26 known viral families that cause human disease' so they can be deployed in 100 days if ther
arXiv:2605.04719v1 Announce Type: new Abstract: Tool-integrated Text-to-SQL parsing has emerged as a promising paradigm, framing SQL generation as a sequential decision-making process interleaved with
This post from Thariq discusses efforts to acquire additional computational resources to improve service delivery, acknowledging that the process may take time. The message suggests commitment to scal
Everything we shipped on security in the past three weeks 🔒 If you wonder what kind of things I care about or am excited about at Replit, just check out the blog and see what our team's been shipping.
arXiv:2605.04664v1 Announce Type: new Abstract: Anomaly detection methods can be very useful in identifying interesting or concerning events. In this work, we develop and examine new probabilistic ano
arXiv:2605.03871v1 Announce Type: new Abstract: Language models encode substantial evaluative knowledge from pretraining, yet current post-training methods rely on external supervision (human annotati
arXiv:2605.04722v1 Announce Type: new Abstract: Input Convex Neural Networks (ICNNs) are commonly used in a two-stage manner: one first trains a convex network and then minimizes it over its input in
arXiv:2605.04501v1 Announce Type: new Abstract: In recent years, object detection has achieved significant progress, especially in the field of open-vocabulary object detection. Unlike traditional met
arXiv:2605.04266v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) typically assumes a static or non-strategic reward model (RM). In iterative deployment, however, the p
arXiv:2605.04904v1 Announce Type: new Abstract: In this paper, we explore deep learning techniques for individual identification of animals based on their skin patterns. Individual identification is c
arXiv:2605.04368v1 Announce Type: new Abstract: Differential temporal difference (TD) methods are value-based reinforcement learning algorithms that have been proposed for infinite-horizon problems. T
arXiv:2605.05082v1 Announce Type: cross Abstract: We externally validated three deep learning models (DenseNet121, ViT-B/32, and ResNet50) for predicting mammographic breast density from breast ultras
arXiv:2605.04651v1 Announce Type: cross Abstract: Adapting pretrained models typically involves a trade-off between the high training costs of backpropagation and the heavy inference overhead of memor
arXiv:2605.04882v1 Announce Type: new Abstract: Automated glaucoma detection is critical for preventing irreversible vision loss and reducing the burden on healthcare systems. However, ensuring fairne
arXiv:2605.04702v1 Announce Type: new Abstract: Identity-preserving text-to-video generation (IPT2V) empowers users to produce diverse and imaginative videos with consistent human facial identity. Des
Research indicates that people frequently follow advice provided by chatbots, yet this compliance with AI recommendations does not correlate with improved outcomes or subjective well-being. This sugge
arXiv:2605.04084v1 Announce Type: new Abstract: Compressing large language models (LLMs) for deployment on commodity GPUs remains challenging: conventional scalar quantization is limited to fixed bit-
arXiv:2506.20911v2 Announce Type: replace Abstract: We develop a cost-efficient neurosymbolic agent to address challenging multi-turn image editing tasks such as ``Detect the bench in the image while
arXiv:2510.00468v4 Announce Type: replace Abstract: We provide evidence that eigenanalysis of the empirical neural tangent kernel (eNTK) can surface feature directions in trained neural networks. Acro
arXiv:2605.04666v1 Announce Type: new Abstract: The objective of this paper is to understand what characteristics and features of clinical data influence physician's decision about ordering laboratory
arXiv:2605.04993v1 Announce Type: new Abstract: Accurate forecasting of electric vehicle (EV) charging demand is critical for grid stability, infrastructure planning, and real-time charging optimizati