All Articles
16750 articles total
A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data
A new neuro-symbolic framework integrates Graph Neural Networks (GNNs) with Relational Bayesian Networks (RBNs) to combine deep learning with probabilistic reasoning.
Human-Aligned Procedural Level Generation Reinforcement Learning via Text-Level-Sketch Shared Representation
VIPCGRL is a deep reinforcement learning framework that uses text, levels, and sketches to create human-aligned procedural content for games.
RL-Struct: A Lightweight Reinforcement Learning Framework for Reliable Structured Output in LLMs
RL-Struct is a lightweight framework using GRPO to align LLMs with structural constraints for reliable JSON output, reducing VRAM usage compared to PPO.
Mechanistic Interpretability of Cognitive Complexity in LLMs via Linear Probing using Bloom's Taxonomy
Study finds that cognitive complexity levels based on Bloom's Taxonomy are linearly separable in the internal representations of LLMs.
The AI Fiction Paradox
The 'AI-Fiction Paradox' explains why autoregressive models struggle with long-form fiction due to failures in narrative causation and emotional architecture.
SciVisAgentBench: A Benchmark for Evaluating Scientific Data Analysis and Visualization Agents
SciVisAgentBench is a new comprehensive benchmark for evaluating AI agents that translate natural language into scientific visualization tasks.
FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment
Investigation into VLM fairness reveals significant racial and gender biases in wellbeing assessments, showing a gap between transparency and equitable outcomes.
When can a power company take your land for data center infrastructure?
A discussion on the legal aspects of power companies exercising eminent domain for data center infrastructure.
LLM-Powered Agentic AI for 5G/6G Networks: A Tutorial and Survey on Architectures, Protocols, and Standardization
A tutorial and survey on integrating LLM-powered agentic AI into 5G/6G network architectures and protocols.
JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models
Introduction of JoyNexus, a multi-tenant service for VLA model post-training that decouples training, inference, and environment services to improve GPU efficiency.
HCIG: A Hierarchical Cross-Modal Incongruity Graph Network for Multimodal Sarcasm and Cyberbullying Detection
Proposed HCIG and GCCN frameworks for multimodal sarcasm and cyberbullying detection using hierarchical cross-modal incongruity graph networks.
DADiff: Diffusion-Driven Cross-Domain Policy Adaptation for Reinforcement Learning
Introduction of DADiff, a diffusion-based framework for cross-domain policy adaptation in reinforcement learning to handle dynamics mismatch.
Understanding Reasoning from Pretraining to Post-Training
Research using chess as a testbed to quantify how pretraining choices affect the returns to RL compute and the nature of reasoning improvements.
A Methodology for Auditable Trustworthiness Levels in AI Lifecycle Governance
A lightweight methodology for creating auditable trustworthiness levels and lifecycle governance in AI systems.
ToolSciVer: Multimodal Scientific Claim Verification with Visual Tool Augmented Reinforcement Learning
ToolSciVer, a framework for multimodal scientific claim verification that uses visual tools and GRPO for enhanced reasoning on scientific visuals.
When Do Multi-Agent Systems Help? An Information Bottleneck Perspective
Theoretical analysis of multi-agent systems versus single-agent systems from an information bottleneck perspective, exploring the trade-off between context reduction and information loss.
An Exam for Active Observers
Introduction of ActiveVision, a benchmark demonstrating that current MLLMs struggle significantly with active visual observation tasks compared to humans.
US gas prices hit an average of $4 a gallon again
US gas prices have returned to an average of $4 per gallon.
Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids
Researchers propose a framework combining random-forest pre-classifiers with actor-critic controllers to manage congestion in low-voltage grids more robustly.
DPNeXt: A Lightweight Multi-Scale Feature Fusion Framework for Efficient ViT-Based Multi-Task Dense Prediction
Introduction of DPNeXt, a lightweight multi-scale feature fusion framework for efficient Vision Transformer-based multi-task dense prediction in robotics.