arXiv:2506.02794v2 Announce Type: replace-cross Abstract: We introduce PhysGaia, a novel physics-aware benchmark for Dynamic Novel View Synthesis (DyNVS) that encompasses both structured objects and unstructured physical phenomena. While existing datasets primarily focus on photorealistic appearance, PhysGaia is specifically designed to support physics-consistent dynamic reconstruction. Our benchmark features complex scenarios with rich multi-body interactions, where objects […]
Beyond Preset Identities: How Agents Form Stances and Boundaries in Generative Societies
arXiv:2603.23406v2 Announce Type: replace Abstract: While large language models simulate social behaviors, their capacity for stable stance formation and identity negotiation during complex interventions remains unclear. To overcome the limitations of static evaluations, this paper proposes a novel mixed-methods framework combining computational virtual ethnography with quantitative socio-cognitive profiling. By embedding human researchers into generative multiagent […]
Generalized Machine Learning for Fast Calibration of Agent-Based Epidemic Models
arXiv:2509.07013v3 Announce Type: replace-cross Abstract: Agent-based models (ABMs) are widely used to study infectious disease dynamics, but their calibration is often computationally intensive, limiting their applicability in time-sensitive public health settings. We propose DeepIMC (Deep Inverse Mapping Calibration), a machine learning-based calibration framework that directly learns the inverse mapping from epidemic time series to epidemiological […]
PBLean: Pseudo-Boolean Proof Certificates for Lean 4
arXiv:2602.08692v2 Announce Type: replace-cross Abstract: We present PBLean, a method for importing VeriPB pseudo-Boolean (PB) proof certificates into Lean 4. Key to our approach is reflection: a Boolean checker function whose soundness is fully proved in Lean and executed as compiled native code. Our method scales to proofs with tens of thousands of steps that […]
Do Phone-Use Agents Respect Your Privacy?
arXiv:2604.00986v2 Announce Type: replace-cross Abstract: We study whether phone-use agents respect privacy while completing benign mobile tasks. This question has remained hard to answer because privacy-compliant behavior is not operationalized for phone-use agents, and ordinary apps do not reveal exactly what data agents type into which form entries during execution. To make this question measurable, […]
Tracking the emergence of linguistic structure in self-supervised models learning from speech
arXiv:2604.02043v1 Announce Type: cross Abstract: Self-supervised speech models learn effective representations of spoken language, which have been shown to reflect various aspects of linguistic structure. But when does such structure emerge in model training? We study the encoding of a wide range of linguistic structures, across layers and intermediate checkpoints of six Wav2Vec2 and HuBERT […]
Crystalite: A Lightweight Transformer for Efficient Crystal Modeling
arXiv:2604.02270v1 Announce Type: cross Abstract: Generative models for crystalline materials often rely on equivariant graph neural networks, which capture geometric structure well but are costly to train and slow to sample. We present Crystalite, a lightweight diffusion Transformer for crystal modeling built around two simple inductive biases. The first is Subatomic Tokenization, a compact chemically […]
GenOM: Ontology Matching with Description Generation and Large Language Model
arXiv:2508.10703v3 Announce Type: replace Abstract: Ontology matching (OM) plays an essential role in enabling semantic interoperability and integration across heterogeneous knowledge sources, particularly in the biomedical domain which contains numerous complex concepts related to diseases and pharmaceuticals. This paper introduces GenOM, a large language model (LLM)-based ontology alignment framework, which enriches the semantic representations of […]
The Reasoning Error About Reasoning: Why Different Types of Reasoning Require Different Representational Structures
arXiv:2603.21736v2 Announce Type: replace Abstract: Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I propose a framework identifying four structural properties of representational systems: operability, consistency, structural preservation, and compositionality. These properties are demanded to different degrees […]
Interpretable Classification via a Rule Network with Selective Logical Operators
arXiv:2408.11918v2 Announce Type: replace-cross Abstract: We introduce the Rule Network with Selective Logical Operators (RNS), a novel neural architecture that employs textbfselective logical operators to adaptively choose between AND and OR operations at each neuron during training. Unlike existing approaches that rely on fixed architectural designs with predetermined logical operations, our selective logical operators treat […]
The Illusion of AI Expertise Under Uncertainty: Navigating Elusive Ground Truth via a Probabilistic Paradigm
arXiv:2601.05500v5 Announce Type: replace Abstract: Benchmarking the capabilities of AI systems, including Large Language Models (LLMs) and Vision Models, typically ignores the impact of uncertainty in the underlying ground truth answers from experts. This ambiguity is not just limited to human preferences, but is also consequential even in safety critical domains such as medicine where […]
Omni-SimpleMem: Autoresearch-Guided Discovery of Lifelong Multimodal Agent Memory
arXiv:2604.01007v2 Announce Type: replace Abstract: AI agents increasingly operate over extended time horizons, yet their ability to retain, organize, and recall multimodal experiences remains a critical bottleneck. Building effective lifelong memory requires navigating a vast design space spanning architecture, retrieval strategies, prompt engineering, and data pipelines; this space is too large and interconnected for manual […]