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New Relative Niño index introduces more robust way to measure El Niño strength
New Relative Niño index introduces more robust way to measure El Niño strength Stephanie Baum Scientific Editor Robert Egan Associate Editor A new El Niño index that provides a more climate-robust measure of the strength of El Niño signals has been released by the European Centre for Medium-Range Weather Forecasts (ECMWF). With the World Meteorological Organization's recent update indicating an 80% likelihood of an El Niño event during June–August 2026 and a 90% probability of this...
Qld man charged under new laws after allegedly planning attack on relative
Brisbane man charged under new state laws after allegedly plotting violent attack on family member Wed 3 Jun 2026 at 4:51pm In short: A 61-year-old Brisbane man has become the second person to be charged under new laws introduced following the Bondi shootings. Atallah Mohaghegh Nahvandi faced a Brisbane court after allegedly planning a violent attack on his ex-wife's nephew. Mr Mohaghegh Nahavandi was denied bail and the matter will return to Richlands Magistrates Court next month.
What Makes a Desired Graph for Relational Deep Learning?
Announce Type: new Abstract: Relational deep learning (RDL) converts relational databases (RDBs) into heterogeneous graphs, but graphs derived directly from database schemas are often not well suited for how graph neural networks (GNNs) perform relational reasoning. We study what makes a relational graph suitable for deep learning and show that schema-derived graphs suffer from two systematic failures: information overload and semantic fragmentation.
The Post-GCN Decade Revisited: Curvature-Stratified Evaluation of Relational Learning
Announce Type: new Abstract: Current evaluation practices in relational learning rely heavily on flat leaderboards that average performance across heterogeneous datasets, implicitly assuming a uniform underlying structure. We show that this assumption introduces systematic bias: it obscures geometry-dependent performance variations and can lead to misleading conclusions about model generalization. In this work, we identify intrinsic geometry as a key latent factor governing model effectiveness.
RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases
arXiv:2606.03040v1 Announce Type: new Abstract: Relational databases underpin modern enterprise, scientific, and healthcare systems, yet predictive machine learning on such data remains challenging due to their multi-table, heterogeneous, and temporal structure. Relational Deep Learning (RDL) addresses this by representing databases as heterogeneous graphs and applying graph neural networks (GNNs) directly. RelBench v2 recently introduced autocomplete tasks -- a practically motivated task...
New Jersey man accused of killing wife with barbell allegedly confessed in messages to relatives: report
A New Jersey man accused of killing his wife with a barbell allegedly admitted to the slaying in messages to family members, detailed a "long-simmering hatred" toward her in an email and then attempted suicide after fleeing the scene, according to court records. Michael A. Kless, 67, was charged with first-degree murder in connection with the death of his wife, 66-year-old Stacy E. Kless, Monmouth County Prosecutor Raymond S. Santiago announced last Friday. According to a probable cause...
OpenRFM: Dissecting Relational In-Context Learning
arXiv:2606.04320v1 Announce Type: new Abstract: Relational Foundation Models (RFMs) promise a single pre-trained predictor that, given any relational database, returns predictions in one forward pass via relational in-context learning (ICL). Yet a substantial gap separates open RFMs from their commercial counterparts, and the origin of this gap has not been systematically understood. We dissect a representative framework, the Relational Transformer (RT), from two perspectives.
COMBINER: Composed Image Retrieval Guided by Attribute-based Neighbor Relations
Announce Type: new Abstract: Composed Image Retrieval (CIR) represents a challenging retrieval task that targets locating specific images through multimodal inputs. Despite recent progress in CIR techniques, prior approaches often overlook cases where images appear visually alike yet differ in attributes, potentially undermining both multimodal feature fusion and similarity modeling. To mitigate this limitation, we design a unified representation of cross-modal features based on attribute...
Question-Aware Evidence Ledgers for Video Relational Reasoning
arXiv:2606.02506v1 Announce Type: new Abstract: The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target identity, and dialogue context rather than a single salient frame. We present a test-time reasoning pipeline built around a strong GPT-5.5 video QA solver and a set of question-aware evidence ledgers. The initial solver answers each question from a uniform video representation, while routed...
On first-order definable operations on relational structures
Announce Type: new Abstract: We survey the definitions and main properties of first-order (FO) definable unary operations on relational structures, called FO-transductions, and of FO-definable binary operations based on disjoint union and Cartesian product. We focus our study on Backwards Translation Theorems and Splitting Theorems that permit to express FO properties of output structures in terms of finitely many FO properties of the corresponding input ones. In the particular cases where...