arXiv:2512.04559v3 Announce Type: replace-cross Abstract: Diffusion models excel at generating high-likelihood samples but often require alignment with downstream objectives. Existing fine-tuning methods for diffusion models significantly suffer from reward over-optimization, resulting in high-reward but unnatural samples and degraded diversity. To mitigate over-optimization, we propose Soft Q-based Diffusion Finetuning (SQDF), a novel KL-regularized RL method for […]
SpatialMem: Metric-Aligned Long-Horizon Video Memory for Language Grounding and QA
arXiv:2601.14895v2 Announce Type: replace-cross Abstract: We present SpatialMem, a memory-centric system for long-horizon, language-grounded retrieval and QA from egocentric video, where metric 3D serves as an interpretable indexing scaffold rather than an explicit mapping objective. Starting from casually captured egocentric RGB video, SpatialMem builds a metric-aligned spatial scaffold for indoor scenes, detects structural 3D anchors […]
CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning
arXiv:2602.24142v2 Announce Type: replace-cross Abstract: Mobile Agents can autonomously execute user instructions, which requires hybrid-capabilities reasoning, including screen summary, subtask planning, action decision and action function. However, existing agents struggle to achieve both decoupled enhancement and balanced integration of these capabilities. To address these challenges, we propose Channel-of-Mobile-Experts (CoME), a novel agent architecture consisting of […]
In-batch Relational Features Enhance Precision in An Unsupervised Medical Anomaly Detection Task
arXiv:2603.05534v1 Announce Type: new Abstract: Confounding pathology with normal anatomical variation remains a significant challenge in unsupervised medical-image anomaly detection, resulting in numerous false positives. To enhance integration of healthy variation, we augment the latent representation of a CNN autoencoder with contextual similarities within a normal cohort through batch-wise hypergraph estimation and a shared-weights graph […]
Can deleterious mutations surf deterministic population waves? A functional law of large numbers for a spatial model of Muller’s ratchet
arXiv:2603.06478v1 Announce Type: cross Abstract: The spatial Muller’s ratchet is a model introduced by Foutel-Rodier and Etheridge to study the impact of cooperation and competition on the fitness of an expanding asexual population. The model is an interacting particle system consisting of particles performing symmetric random walks that reproduce and die with rates that depend […]
A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention
arXiv:2603.06567v1 Announce Type: cross Abstract: Machine-learning interatomic potentials (MLIPs) have advanced rapidly, with many top models relying on strong physics-based inductive biases. However, as models scale to larger systems like biomolecules and electrolytes, they struggle to accurately capture long-range (LR) interactions, leading current approaches to rely on explicit physics-based terms or components. In this work, […]
Mitigating Content Effects on Reasoning in Language Models through Fine-Grained Activation Steering
arXiv:2505.12189v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit reasoning biases, often conflating content plausibility with formal logical validity. This can lead to wrong inferences in critical domains, where plausible arguments are incorrectly deemed logically valid or vice versa. This paper investigates how content biases on reasoning can be mitigated through activation steering, an […]
PepEDiff: Zero-Shot Peptide Binder Design via Protein Embedding Diffusion
arXiv:2601.13327v2 Announce Type: replace Abstract: We present PepEDiff, a novel peptide binder generator that designs binding sequences given a target receptor protein sequence and its pocket residues. Peptide binder generation is critical in therapeutic and biochemical applications, yet many existing methods rely heavily on intermediate structure prediction, adding complexity and limiting sequence diversity. Our approach […]
Adversarial Batch Representation Augmentation for Batch Correction in High-Content Cellular Screening
arXiv:2603.05622v1 Announce Type: cross Abstract: High-Content Screening routinely generates massive volumes of cell painting images for phenotypic profiling. However, technical variations across experimental executions inevitably induce biological batch (bio-batch) effects. These cause covariate shifts and degrade the generalization of deep learning models on unseen data. Existing batch correction methods typically rely on additional prior knowledge […]
Towards Neural Graph Data Management
arXiv:2603.05529v1 Announce Type: cross Abstract: While AI systems have made remarkable progress in processing unstructured text, structured data such as graphs stored in databases, continues to grow rapidly yet remains difficult for neural models to effectively utilize. We introduce NGDBench, a unified benchmark for evaluating neural graph database capabilities across five diverse domains, including finance, […]
Boosting deep Reinforcement Learning using pretraining with Logical Options
arXiv:2603.06565v1 Announce Type: new Abstract: Deep reinforcement learning agents are often misaligned, as they over-exploit early reward signals. Recently, several symbolic approaches have addressed these challenges by encoding sparse objectives along with aligned plans. However, purely symbolic architectures are complex to scale and difficult to apply to continuous settings. Hence, we propose a hybrid approach, […]
The DSA’s Blind Spot: Algorithmic Audit of Advertising and Minor Profiling on TikTok
arXiv:2603.05653v1 Announce Type: cross Abstract: Adolescents spend an increasing amount of their time in digital environments where their still-developing cognitive capacities leave them unable to recognize or resist commercial persuasion. Article 28(2) of the Digital Service Act (DSA) responds to this vulnerability by prohibiting profiling-based advertising to minors. However, the regulation’s narrow definition of “advertisement” […]