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Bailey Lipschultz / Bloomberg: Filing: SpaceX aims to raise 75B in its IPO, selling 555.6M shares at 135 each, which would value the company at almost 1.77T — SpaceX is seeking to raise 75 billion in

arXiv:2606.02684v1 Announce Type: cross Abstract: On-Policy distillation (OPD) in large language models is shifting from full-trace KL supervision toward more selective training paradigms. Recent OPD

arXiv:2511.13391v4 Announce Type: replace-cross Abstract: Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a centra

arXiv:2606.03821v1 Announce Type: new Abstract: Active learning is now standard practice in labeling ecological data, enabling ecologists to quickly process large volumes of field data to understand a

Fine-tuning to production inference is the gap where teams get stuck. At #MSBuild today, our own Rob Ferguson, @danielhanchen (@UnslothAI) and @marksaroufim (@coreautoai) discuss: model customization

arXiv:2606.03184v1 Announce Type: cross Abstract: Financial forecasting is difficult due to low signal-to-noise ratios, latent factors, heavy tails, regime shifts, and jumps. Real-world benchmarks off

Fireworks on Microsoft Foundry 1P is GA-ed today! This is after 9 months of hard work to bring Fireworks platform to fully integrated with Microsoft Foundry. We offer the frontier specialized intellig

A major consulting firm (Bain) has found that corporate returns on AI investments are underwhelming, following similar findings from MIT and McKinsey. This suggests that despite significant spending a

arXiv:2606.02658v1 Announce Type: new Abstract: This paper introduces an estimation and control framework for dynamic landing of multi-rotor uncrewed aerial vehicles on moving platforms. The proposed

arXiv:2606.02837v1 Announce Type: cross Abstract: Accurate translation from Natural Language to First-Order Logic (NL-to-FOL) underpins neurosymbolic AI systems and Natural Language Inference (NLI), m

arXiv:2606.03852v1 Announce Type: cross Abstract: Large language models often generate code with bugs. Existing methods rely on feedback signals such as test failures and self-critiques to iteratively

arXiv:2606.03939v1 Announce Type: cross Abstract: Federated Learning (FL) of foundation and edge models increasingly targets deployments where client data distributions drift over time, yet existing f

arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T

arXiv:2606.03393v1 Announce Type: new Abstract: We propose a novel diffusion model, Flicker-DDPM, which incorporates flicker (1/f) noise inspired by self-organized criticality (SOC), a widely observed

arXiv:2606.03330v1 Announce Type: cross Abstract: Literature reveals that a Large Language Model's (LLM) behavior is not only conditioned by its original weights but also its instance-level parameters

This article explores the historical development and origins of floating-point number representation in computing, likely covering how early computer scientists and engineers designed methods to repre

arXiv:2604.07366v2 Announce Type: replace Abstract: Partial differential equations (PDEs) govern nearly every physical process in science and engineering, but solving them at scale remains prohibitive

arXiv:2606.03430v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) deployed in energy infrastructure are vulnerable to model theft attacks, which al

arXiv:2606.03216v1 Announce Type: new Abstract: We study preference alignment for image inpainting. Rather than proposing yet another method, we revisit the problem from first principles and reassess

arXiv:2606.03919v1 Announce Type: cross Abstract: Understanding and anticipating scientific change requires models that distinguish between endogenous consolidation and exogenous diffusion of scientif

arXiv:2606.03453v1 Announce Type: cross Abstract: Vulnerability disclosure volumes now far exceed organizational assessment capacity, yet three adjacent research communities (proof-of-concept generati

arXiv:2606.02860v1 Announce Type: cross Abstract: Catastrophic forgetting is often framed as a representational problem: after sequential training, a model appears to lose the features that supported

arXiv:2606.03976v1 Announce Type: cross Abstract: Representations of the world, arguably, contain information about features (e.g. something is blue, something is a circle) but also information about

arXiv:2606.03761v1 Announce Type: new Abstract: Frame analysis of migration news is a socially consequential task: media scholars and researchers who study how migration is narrated need tools that ar

arXiv:2606.03254v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) allows efficient and high-fidelity novel view synthesis (NVS) from an offline recorded image sequence. However

Fresh Open weight model drop😋 Introducing Ideogram 4.0: the best open image model in the world. Think it. Make it. Own it. Download the weights, fine-tune on your own data, and run it on your hardware

arXiv:2606.03460v1 Announce Type: new Abstract: Underground coal mining requires personnel and heavy equipment to operate within shared, confined, and poorly illuminated spaces where hazards such as e

arXiv:2606.03660v1 Announce Type: new Abstract: Large language models are increasingly used as chemistry assistants, yet most chemistry benchmarks still score only final answers. This masks a critical

The past year was about building agents. The next year is about putting them to work. Organizations have moved quickly from experimenting with AI agents to building ones that perform complex business

arXiv:2606.03777v1 Announce Type: new Abstract: AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, be

arXiv:2606.02764v1 Announce Type: new Abstract: Satellite-derived bathymetry (SDB) from multispectral imagery is cost-effective but scales poorly across regions, especially in optically complex coasta

arXiv:2606.03097v1 Announce Type: new Abstract: Incorporating news into time series forecasting is appealing because news can reveal abrupt exogenous events that historical values alone cannot recover

arXiv:2606.02948v1 Announce Type: new Abstract: Curvature adaptivity is a classical theme in online optimization: for convex Lipschitz losses, adaptive methods interpolate between the optimal O(sqrt{T

arXiv:2603.27455v2 Announce Type: replace Abstract: In this paper, we introduce NAS3R, a self-supervised feed-forward framework that jointly learns explicit 3D geometry and camera parameters with no g

arXiv:2606.03557v1 Announce Type: new Abstract: As generative AI capabilities expand, AI-driven virtual worlds face a growing architectural challenge. Users interact through in-world interfaces in mul

arXiv:2606.03304v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated in multilingual settings, yet their inference behavior in low-resource African languages remains

arXiv:2604.04974v2 Announce Type: replace Abstract: Video is a scalable observation of physical dynamics: it captures how objects move, how contact unfolds, and how scenes evolve under interaction --

arXiv:2606.03876v1 Announce Type: cross Abstract: With the growing prevalence of modern ubiquitous computing technologies, multi-modal tracking systems hold promise for providing timely awareness and

Frontier models are powerful advisors. On @harvey's Legal Agent Benchmark, a GLM 5.1 worker using Claude Opus 4.7 as a sparse advisor reached 18/100 all-pass versus 14/100 for Opus alone, at 39% of th

arXiv:2606.02615v1 Announce Type: cross Abstract: Few-shot prompting provides an effective way to adapt auditory large language models to low-resource tasks such as children's speech recognition. Howe

arXiv:2606.03165v1 Announce Type: cross Abstract: The language used by digital chat assistants such as ChatGPT can diverge from human expectations (misalignment). Research, mostly on Scientific Englis

Fundamental's NEXUS is a foundation model designed specifically for tabular data, trained on billions of tabular datasets using Amazon SageMaker HyperPod to understand non-linear relationships across

arXiv:2512.11213v2 Announce Type: replace Abstract: Scaling test-time computation has been shown to significantly improve large language model (LLM) performance without additional training. However, e

arXiv:2606.03078v1 Announce Type: new Abstract: Effective document-level machine translation (DocMT) requires capturing long-range discourse dependencies. Recent work has explored retrieval-based and

arXiv:2606.03921v1 Announce Type: new Abstract: Converting multi-view RGB observations into simulation-ready 3D environments remains challenging because current reconstruction pipelines produce monoli

arXiv:2606.02959v1 Announce Type: new Abstract: Published evaluations of prompt-injection and jailbreak detectors for Large Language Models often suffer from two systematic weaknesses: per-dataset thr