Backstage with Lakebase, part 2
This article is the second installment in a series exploring Lakebase, Databricks' data management solution, providing behind-the-scenes insights into its architecture, capabilities, or integration wi
Knowledge catalogue
This article is the second installment in a series exploring Lakebase, Databricks' data management solution, providing behind-the-scenes insights into its architecture, capabilities, or integration wi
arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v
arXiv:2605.14883v1 Announce Type: cross Abstract: Mild traumatic brain injury (mTBI) is a prevalent condition that remains difficult to diagnose in its early stages. Oculomotor dysfunction is a well-e
arXiv:2605.14146v1 Announce Type: new Abstract: bde is a user-friendly Python package for Bayesian Deep Ensembles with a particular focus on tabular data. Built on an efficient JAX implementation of t
arXiv:2605.14438v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures enhance the efficiency of large language models by activating only a subset of experts per token. However, standa
Beau Rothrock had been at @AngelList for two months when he walked into a Redshift-to-Snowflake migration in deep trouble, already two months behind schedule. He had a 5-week window to migrate all 14,
arXiv:2605.14417v1 Announce Type: cross Abstract: Natural language is an intuitive interface for humanoid robots, yet streaming whole-body control requires control representations that are executable
arXiv:2605.14106v1 Announce Type: new Abstract: We investigate whether behavior cloning is sufficient to produce active perception in a structured object-finding task. A low-cost robot arm equipped wi
arXiv:2605.14944v1 Announce Type: new Abstract: With the growth of the construction industry and the global shortage of skilled labor, the automation of crane control has become increasingly important
arXiv:2602.19532v2 Announce Type: replace Abstract: Real-world tasks involve nuanced combinations of goal and safety specifications. In high dimensions, the challenge is exacerbated: formal automata b
Beware the empathy exploit. Empathy is good and right when thought through (deep), but can be deadly to civilization when simply stimulus-response (shallow). For example, releasing a repeat violent of
arXiv:2605.14791v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) agents are pushing AI beyond tools toward autonomous scientific discovery. We discuss two complementar
arXiv:2605.14311v1 Announce Type: cross Abstract: Test-Time Scaling (TTS), which samples multiple candidate actions and ranks them via a Critic Model, has emerged as a promising paradigm for generalis
arXiv:2603.28205v2 Announce Type: replace Abstract: Aspect-Based Sentiment Analysis (ABSA) faces critical challenges due to representation entanglement and false-negative collisions in real-valued emb
// Beyond Individual Intelligence // One of the more useful multi-agent surveys I've read this year. 200+ papers mapped along three axes: collaboration mechanisms, failure attribution, and self-evolut
arXiv:2605.14892v1 Announce Type: new Abstract: LLM-based autonomous agents have demonstrated strong capabilities in reasoning, planning, and tool use, yet remain limited when tasks require sustained
arXiv:2605.14654v1 Announce Type: new Abstract: Self-supervised pre-training methods in medical imaging typically treat each individual as an isolated instance, learning representations through augmen
arXiv:2605.13935v1 Announce Type: cross Abstract: Diffusion language models are a promising alternative to autoregressive models, yet post-training methods for them largely adapt reward-maximizing obj
arXiv:2510.02837v2 Announce Type: replace Abstract: Although recent tool-augmented benchmarks involve complex requests, evaluation remains limited to answer matching, neglecting critical trajectory as
arXiv:2605.14773v1 Announce Type: cross Abstract: Data selection accelerates training by identifying representative training data while preserving model performance. However, existing methods mainly f
arXiv:2605.14886v1 Announce Type: new Abstract: Electrocardiogram (ECG) monitoring in Internet of Medical Things (IoMT) networks is constrained by strict data-sharing regulations and privacy concerns.
Big move from arXiv: a one-year ban for authors who submit AI-generated content without proper checking. This is not about banning AI from academia. AI can be extremely useful. It can help us write be
Amy Thomson / Bloomberg: Bill Ackman says his fund has taken a new stake in Microsoft after the company's recent share price decline; Ackman says investors have underestimated Microsoft — Bill Ackman
California's AB 1921 (Protect Our Games Act), introduced in February 2026, would require publishers to take responsibility for the long-term playability of online games. The bill passed a key hurdle o
arXiv:2605.14772v1 Announce Type: new Abstract: Understanding human motion beyond surface kinematics is crucial for motion analysis, rehabilitation, and injury risk assessment. However, progress in th
BiRefNet is a boundary refinement network model integrated into ComfyUI, likely designed for precise image segmentation and edge detection tasks. The model appears to be used as a node within ComfyUI'
arXiv:2605.13859v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer promising energy-efficient alternatives to large language models (LLMs) due to their event-driven nature and ultr
arXiv:2506.05762v5 Announce Type: replace Abstract: Recent advances in offline Reinforcement Learning (RL) have proven that effective policy learning can benefit from imposing conservative constraints
Blogs lose authenticity and engagement when attributed to anonymous teams rather than named individual authors, as personal ownership creates accountability and stronger reader connection. The post su
arXiv:2605.14169v1 Announce Type: new Abstract: Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling)
Three years of enterprise AI investment, and most companies are still waiting for the payoff. Boomi LP thinks it has found it, unveiling Boomi Companion, a collection of open-source agent skills that
arXiv:2508.02332v3 Announce Type: replace Abstract: The performance of Bayesian optimization (BO), a highly sample-efficient method for expensive black-box problems, is critically governed by the sele
arXiv:2602.04265v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for enhancing reasoning in Large Language Models (LL
arXiv:2605.15012v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought roll
arXiv:2605.14555v1 Announce Type: cross Abstract: Current methods for creating drum loop audio in digital music production, such as using one-shot samples or resampling, often demand non-trivial effor
arXiv:2605.14709v1 Announce Type: new Abstract: Recent unified models integrate multimodal understanding and generation within a single framework. However, an 'understanding-generation gap' persists,
arXiv:2605.13887v1 Announce Type: cross Abstract: Transformer-based Spiking Neural Networks (SNNs) integrate SNNs with global self-attention and have demonstrated impressive performance. However, exis
arXiv:2601.21174v2 Announce Type: replace Abstract: Entity alignment (EA) is critical for knowledge graph (KG) fusion. Existing EA models lack transferability and are incapable of aligning unseen KGs
BREAKING: The results are in for Slides Arena... @AnthropicAI and @Zai_org models continue to lead the way in soft-verifiable domains 1st: Opus 4.7 by @AnthropicAI 2nd: Opus 4.7 (Thinking) by @Anthrop
arXiv:2605.14569v1 Announce Type: new Abstract: Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neur
arXiv:2605.14049v1 Announce Type: new Abstract: The growing adoption of large language models in legal practice brings both significant promise and serious risk. Legal professionals stand to benefit f
arXiv:2605.14108v1 Announce Type: cross Abstract: Diabetic Retinopathy (DR) is one of the leading causes of preventable blindness, yet rural regions often lack the specialists and infrastructure neede
Bring Cava here Soulva being so popular on Doordash is a sign of SF's lack of variety when it comes to quick dining options. Their meats are drier than sand, their kale is rigid and bitter. It's such
Learn about the experimental general-purpose accessibility agent that GitHub is piloting. The post Building a general-purpose accessibility agent—and what we learned in the process appeared first on T
By far the most embarrassing thing about this is that the hedge fund guy was using the MOST CRINGE website on the entire Internet for milf sex 😬 https://x.com/i/grok/share/4c2a52a147a34114a8db49c92f24
arXiv:2605.13918v1 Announce Type: cross Abstract: Automated game testing is important for verifying game functionality, but it remains a costly and time-consuming process. Manual testing often misses
arXiv:2602.18435v2 Announce Type: replace Abstract: Clustering is widely used for unsupervised structure discovery, yet it offers limited insight into how reliable each individual assignment is. Diagn
arXiv:2605.14615v1 Announce Type: new Abstract: Camera calibration is a fundamental prerequisite for reliable geometric perception, yet classical approaches rely on controlled acquisition setups that
arXiv:2605.14810v1 Announce Type: new Abstract: In obstacle avoidance navigation of unmanned aerial vehicles (UAVs), variations in obstacle scale have received strangely less attention than obstacle n
arXiv:2511.07308v2 Announce Type: replace Abstract: Understanding the training dynamics of deep neural networks remains a major open problem, with physics-inspired approaches offering promising insigh
arXiv:2605.14799v1 Announce Type: new Abstract: In recent years, computer vision has witnessed remarkable progress, fueled by the development of innovative architectures such as Convolutional Neural N
arXiv:2512.11484v1 Announce Type: cross Abstract: This paper reveals and exploits a critical security vulnerability: the electromagnetic (EM) side channel of capacitive touchscreens leaks sufficient i
arXiv:2605.15041v1 Announce Type: new Abstract: Tool use extends large language models beyond parametric knowledge, but reliable execution requires balancing appropriate reasoning depth with strict st
arXiv:2605.14537v1 Announce Type: new Abstract: We introduce extsc{Cattle Trade, a multi-agent benchmark for evaluating large language models (LLMs) as agents in strategic reasoning under imperfect in
arXiv:2605.15141v1 Announce Type: new Abstract: Real-time interactive video generation requires low-latency, streaming, and controllable rollout. Existing autoregressive (AR) diffusion distillation me
arXiv:2605.15133v1 Announce Type: new Abstract: Causal inference, estimating causal effects from observational data, is a fundamental tool in many disciplines. Of particular importance across a variet
arXiv:2602.09969v2 Announce Type: replace Abstract: We study a canonical multi-task demand-learning problem motivated by retail pricing, where a firm seeks to estimate heterogeneous linear price-respo
arXiv:2509.20846v3 Announce Type: replace Abstract: Time series generation (TSG) synthesizes realistic sequences and has achieved remarkable success. Among TSG, conditional models generate sequences g
arXiv:2602.20571v2 Announce Type: replace Abstract: Many benchmarks for automated causal inference evaluate a system's performance based on a single numerical output, such as an Average Treatment Effe
arXiv:2602.04473v2 Announce Type: replace Abstract: Recently, diffusion models have brought novel insights to pan-sharpening and notably boosted fusion precision. However, most existing models perform