BEAVER: An Enterprise Benchmark for Text-to-SQL
arXiv:2409.02038v3 Announce Type: replace-cross Abstract: Existing text-to-SQL benchmarks have largely been constructed from public databases with well-structured schemas and simplistic question-SQL p
Knowledge catalogue
arXiv:2409.02038v3 Announce Type: replace-cross Abstract: Existing text-to-SQL benchmarks have largely been constructed from public databases with well-structured schemas and simplistic question-SQL p
arXiv:2605.12726v1 Announce Type: new Abstract: Final-token safety probes monitor a single hidden state after prompt prefill, but jailbreak prompts can contain probe-visible unsafe evidence distribute
arXiv:2605.12730v1 Announce Type: new Abstract: Existing AI systems for modeling human behavior operate at the level of individuals or detect events after they occur. As a result, they systematically
arXiv:2510.01502v2 Announce Type: replace-cross Abstract: Current video foundation models, including the strongest self-supervised models such as V-JEPA2, fail to capture how humans organize social in
Yesterday, in Musk v. Altman, before the jurors came in, Sam Altman's team passed up what looked - from a distance - like a little league trophy. It was not. Yvonne Gonzalez Rogers had the lawyers rea
Sam Altman shared a personal reflection on fatherhood, expressing that being a dad has surpassed his already-high expectations more than any other experience in his life. The post highlights how paren
being vulnerable - by far one of the most important applied ai fields is in AI x Healthcare, but nobody on my team knows how to cover it! very fortunate to have @jacobeffron on the pod for this one -
arXiv:2605.12710v1 Announce Type: new Abstract: Residual risk metrics have recently been introduced to assess the safety implications of automated driving systems. Existing approaches typically assume
arXiv:2512.18951v3 Announce Type: replace Abstract: Infants learn not only object categories but also fine-grained visual attributes such as color, size, and texture from limited experience. Prior inf
arXiv:2605.13574v1 Announce Type: cross Abstract: This study investigates deep self-disclosure toward generative AI by examining perceived non-humanity and structural similarity as psychological facto
arXiv:2605.12894v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in settings where they interact with a wide variety of people, including users who are uncle
arXiv:2605.13520v1 Announce Type: cross Abstract: We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via
arXiv:2605.12512v1 Announce Type: cross Abstract: Driven by large language models (LLMs), social bot can autonomously engage in local interactions, whose human-like behaviors enable them to evade soci
arXiv:2605.13383v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) perform computations on graphs by routing the signal between graph regions using a graph shift operator or a message passin
arXiv:2605.13652v1 Announce Type: cross Abstract: Pre-training large language models is dominated by the memory cost of storing full-rank weights, gradients, and optimizer states. Low-rank pre-trainin
arXiv:2509.24728v2 Announce Type: replace Abstract: Latent categorical variables are frequently found in deep learning architectures. They can model actions in discrete reinforcement-learning environm
arXiv:2605.13525v1 Announce Type: cross Abstract: Automated driving has made remarkable progress, yet situations still arise where human intervention is necessary. Teleoperation provides a scalable so
arXiv:2603.05582v2 Announce Type: replace-cross Abstract: The issue of algorithmic biases in deep learning has led to the development of various debiasing techniques, many of which perform complex tra
Big increases in message discipline across all the AI labs in recent weeks, an inevitable outcome of the labs being subject to increased scrutiny. Much more boring than the oracular mutterings or Disc
big launches today! 🚀Launching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests
arXiv:2605.12534v1 Announce Type: cross Abstract: Most work in audio enhancement targets human speech, while bioacoustics is less studied due to noisy recordings and the distinct traits of animal soun
arXiv:2605.12804v1 Announce Type: new Abstract: Positive-negative pressure regulation is critical to soft robotic actuators, enabling large motion ranges and versatile actuation modes. However, achiev
arXiv:2605.13794v1 Announce Type: cross Abstract: We present BlitzGS, a distributed 3DGS framework that reduces active Gaussian workload for fast city-scale reconstruction. BlitzGS manages this worklo
arXiv:2506.13456v2 Announce Type: replace Abstract: Diffusion Policy has demonstrated strong visuomotor modeling capabilities, but its high computational cost renders it impractical for real-time robo
arXiv:2605.13382v1 Announce Type: new Abstract: While autoregressive (AR) Vision-Language-Action (VLA) models have demonstrated formidable reasoning capabilities in robotic tasks, their sequential dec
Agent governance has gone from niche concern to boardroom prerequisite — and the enterprises that saw it coming are now pulling ahead. The rise of agentic AI across enterprise operations has made gove
arXiv:2605.12520v1 Announce Type: cross Abstract: Taxonomy induction is crucial for organizing concepts into explicit and interpretable semantic hierarchies. While existing methods have achieved promi
arXiv:2605.13669v1 Announce Type: cross Abstract: This paper proposes a nonlinear guidance strategy capable of intercepting a constant-velocity, non-maneuvering target while strictly satisfying the pr
arXiv:2605.12560v1 Announce Type: cross Abstract: Improving patient outcomes depends on the prompt and accurate diagnosis of brain tumors, but manual MRI scan analysis is still time-consuming and unre
arXiv:2605.13059v1 Announce Type: new Abstract: Clinical diagnostic workups typically follow a modality escalation pathway: after initial clinical evaluation, clinicians begin with routine structural
arXiv:2605.13054v1 Announce Type: cross Abstract: Cross-domain offline reinforcement learning aims to adapt a policy from a source domain to a target domain using only pre-collected datasets, where en
arXiv:2605.12517v1 Announce Type: cross Abstract: Vision-language models (VLMs) are often deployed on text-only inputs, although they are trained with images. We find that removing the vision modality
U.K.-based artificial intelligence inference chip startup Fractile Ltd. said today it has closed on a 220 million Series B round of funding. The company was founded in 2022 by the Oxford University-tr
Build dashboards and automations from your Snowflake data for pipeline analysis, product usage, customer segments, and more. Admins maintain control over access, business definitions, and shared data
arXiv:2605.13360v1 Announce Type: new Abstract: There is a growing demand for agentic AI technologies for a range of downstream applications like customer service and personal assistants. For applicat
built a bird search app to show off pinecone's full text search capabilities 2,079 bird articles, full-text keyword search, Gemini Embedding 2 for cross-modal visual search. the birds did not consent
arXiv:2605.13283v1 Announce Type: new Abstract: We revisit Byzantine robust distributed estimation for high-dimensional sparse linear models. By combining local ell_1-regularized robust estimation wit
arXiv:2605.13544v1 Announce Type: new Abstract: Fine-grained Vision-Language Pre-training (FVLP) demonstrates significant potential in 3D medical image understanding by aligning anatomy-level visual r
arXiv:2508.01031v5 Announce Type: replace Abstract: Computer-Aided Design (CAD) is widely used for conceptual design and parametric 3D modeling, but typically requires a high level of expertise from d
arXiv:2605.13208v1 Announce Type: new Abstract: Efficient Gas Source Localization (GSL) in real-world settings is crucial, especially in emergency scenarios. Mobile robots equipped with low-cost, in-s
Bloomberg: California Gov. Gavin Newsom proposes a new 7.25% tax on web-based software sales, targeting $1.1B in state and local tax revenue in the upcoming budget year — California Governor Gavin New
arXiv:2605.12507v1 Announce Type: cross Abstract: While Large Language Model (LLM) multi-agent systems (MAS) offer a transformative approach to simulating human behavior in complex systems, it remains
arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,
arXiv:2410.14375v3 Announce Type: replace Abstract: Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlati
arXiv:2605.13589v1 Announce Type: cross Abstract: Causal discovery, the problem of inferring the direction of causality, is generally ill-posed. We use the language of structural causal models (SCM) t
arXiv:2605.13646v1 Announce Type: cross Abstract: End-to-end autonomous driving, which bypasses traditional modular pipelines by directly predicting future trajectories from sensor inputs, has recentl
arXiv:2605.12580v1 Announce Type: new Abstract: Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing randomly initialized input-to-hidden weights, which permi
arXiv:2508.01049v2 Announce Type: replace Abstract: Independent on-policy policy gradient algorithms are widely used for multi-agent reinforcement learning (MARL) in cooperative and no-conflict games,
CJ Haddad / CNBC: Cerebras co-founders CEO Andrew Feldman and CTO Sean Lie own stakes worth 3.2B and 1.7B, respectively, representing about 5.5% and 3% of the company — The tech billionaires club has
Jordan Novet / CNBC: Cerebras pops 68% in Nasdaq debut, pushing the AI chipmaker's market cap to 95 billion … Cerebras Systems soared 68% in its Nasdaq debut on Thursday, closing at 311.07 after selli
Cerebras Systems Inc. has officially priced its stock at 185 per share ahead of the most anticipated initial public offering of the year today, well above its expected range of between 150 and 160 per
Bloomberg: Cerebras shares closed up 68% at 311.07 in the company's Nasdaq debut after it raised 5.5B in the year's largest IPO, giving it a market value of 67B — Cerebras Systems Inc. shares jumped 6
Updated with opening stock price: Cerebras Systems Inc. today opened trading as a public company at 350 a share, 89% above its offering price, as it kicked off what looks like a huge year for initial
arXiv:2605.12876v1 Announce Type: new Abstract: Randomized smoothing provides strong, model-agnostic robustness certificates, but existing guarantees are limited to single modalities, treating continu
arXiv:2605.12718v1 Announce Type: new Abstract: Multi-agent debate has emerged as a promising approach for improving LLM reasoning on ground-truth tasks, yet current methodologies face certain structu
arXiv:2605.12553v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for improving the reliability and spectral efficiency of massive MIMO-OFDM systems in
arXiv:2509.23597v5 Announce Type: replace-cross Abstract: Time series forecasting remains a critical challenge across numerous domains, yet the effectiveness of complex models often varies unpredictab
arXiv:2605.13675v1 Announce Type: new Abstract: Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. Ho
arXiv:2406.05410v3 Announce Type: replace Abstract: Current multimodal large language models (MLLMs) are mainly focused on the understanding and processing of perceptual modalities such as images and
arXiv:2605.13262v1 Announce Type: new Abstract: Modern SMILES-based chemical language models obtain strong MoleculeNet performance by treating SMILES as generic text and compensating with multi-millio