arXiv:2505.01700v3 Announce Type: replace-cross Abstract: Existing protein-ligand docking studies typically focus on the self-docking scenario, which is less practical in real applications. Moreover, some studies involve heavy frameworks requiring extensive training, posing challenges for convenient and efficient assessment of docking methods. To fill these gaps, we design PoseX, an open-source benchmark to evaluate both self-docking […]
AI-Derived Reproductive Phenotypes and Explainable ML for Concurrent Early Multimorbidity in U.S. Women: NHANES 2017-March 2020
arXiv:2604.22890v1 Announce Type: new Abstract: Background:Adverse reproductive history is a multisystemic risk factor, but evidence is constrained by isolated outcome studies, limited adjustment, and non-interpretable algorithmic models. We re-frame the estimand from prediction to concurrent risk classification and emphasize calibration, interpretability, and systematic error. Methods:We analyzed 1,602 U.S. women aged 20-44 years from NHANES 2017-March […]
MetaEarth3D: Unlocking World-scale 3D Generation with Spatially Scalable Generative Modeling
arXiv:2604.22828v1 Announce Type: cross Abstract: Recent generative AI models have achieved remarkable breakthroughs in language and visual understanding. However, although these models can generate realistic visual content, their spatial scale remains confined to bounded environments, preventing them from capturing how geographic environments evolve across thousands of kilometers or from modeling the spatial structure of the […]
Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment
arXiv:2604.24178v1 Announce Type: cross Abstract: Multi-Objective Alignment aims to align Large Language Models (LLMs) with diverse and often conflicting human values by optimizing multiple objectives simultaneously. Existing methods predominantly rely on static preference weight construction strategies. However, rigidly aligning to fixed targets discards valuable intermediate information, as training responses inherently embody valid preference trade-offs even […]
Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors
arXiv:2603.21768v3 Announce Type: replace-cross Abstract: Precipitation nowcasting is critical for disaster mitigation and aviation safety. However, radar-only models frequently suffer from a lack of large-scale atmospheric context, leading to performance degradation at longer lead times. While integrating meteorological variables predicted by weather foundation models offers a potential remedy, existing architectures fail to reconcile the profound […]
Hierarchical Behaviour Spaces
arXiv:2604.24558v1 Announce Type: new Abstract: Recent work in hierarchical reinforcement learning has shown success in scaling to billions of timesteps when learning over a set of predefined option reward functions. We show that, instead of using a single reward function per option, the reward functions can be effectively used to induce a space of behaviours, […]
Right-to-Act: A Pre-Execution Non-Compensatory Decision Protocol for AI Systems
arXiv:2604.24153v1 Announce Type: new Abstract: Current AI systems increasingly operate in contexts where their outputs directly trigger real-world actions. Most existing approaches to AI safety, risk management, and governance focus on post-hoc validation, probabilistic risk estimation, or certification of model behavior. However, these approaches implicitly assume that once a decision is produced, it is eligible […]
Certified geometric robustness — Super-DeepG
arXiv:2604.24379v1 Announce Type: new Abstract: Safety-critical applications are required to perform as expected in normal operations. Image processing functions are often required to be insensitive to small geometric perturbations such as rotation, scaling, shearing or translation. This paper addresses the formal verification of neural networks against geometric perturbations on their image dataset. Our method Super-DeepG […]
RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support
arXiv:2604.22800v1 Announce Type: cross Abstract: Motivation: Structural Biologists have contributed more than 245,000 experimentally determined three-dimensional structures of biological macromolecules to the Protein Data Bank (PDB). Incoming data are validated and biocurated by ~20 expert biocurators across the wwPDB. RCSB PDB biocurators who process more than 40% of global depositions face increasing challenges in maintaining […]
QED: An Open-Source Multi-Agent System for Generating Mathematical Proofs on Open Problems
arXiv:2604.24021v1 Announce Type: new Abstract: We explore a central question in AI for mathematics: can AI systems produce original, nontrivial proofs for open research problems? Despite strong benchmark performance, producing genuinely novel proofs remains an outstanding challenge for LLMs. Through systematic experiments with frontier LLMs on research-level proof tasks, we identify seven failure modes that […]
Implicit Humanization in Everyday LLM Moral Judgments
arXiv:2604.22764v1 Announce Type: cross Abstract: Recent adoption of conversational information systems has expanded the scope of user queries to include complex tasks such as personal advice-seeking. However, we identify a specific type of sought advice-a request for a moral judgment (i.e. “who was wrong?”) in a social conflict-as an implicitly humanizing query which carries potentially […]
The Spectral Lifecycle of Transformer Training: Transient Compression Waves, Persistent Spectral Gradients, and the Q/K–V Asymmetry
arXiv:2604.22778v1 Announce Type: cross Abstract: We present the first systematic study of weight matrix singular value spectra emphduring transformer pretraining, tracking full SVD decompositions of every weight matrix at 25-step intervals across three model scales (30M–285M parameters). We discover three phenomena: textbf(1)~Transient Compression Waves: stable rank compression propagates as a traveling wave from early to […]