All Articles
16770 articles total
NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoning
NeurOWL is introduced as a neuro-symbolic framework to handle reasoning in incomplete OWL ontologies using LLMs and ontology embeddings.
AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets
AgentFAIR is a multi-agent framework designed to evaluate the FAIRness (Findability, Accessibility, Interoperability, Reusability) of geospatial datasets.
Knowledge-Centric Agents for Workflow Generation
A new knowledge-centric framework for generating visual creation workflows (e.g., for ComfyUI) using knowledge inversion and injection.
DSWorld: A Data Science World Model for Efficient Autonomous Agents
DSWorld introduces a world model for data science to predict environment state transitions, significantly accelerating agent training and inference.
A Formally Grounded ODRL Evaluator: Implementation and Comparison
Researchers implement a formally grounded ODRL evaluator to provide consistent and interoperable policy evaluation for data access in European dataspaces.
Closing the AI Trust Gap: The Case for Independent Certification for Trustworthy AI
A proposal for independent certification of trustworthy AI to close the gap between internal corporate responsible AI practices and external verifiable outcomes.
SciForge: An AI-Native, Multimodal Workbench for Scientific Discovery
SciForge is an open-source, multimodal AI workbench designed for scientific discovery, integrating agentic research sprints and evidence governance.
Power companies are using eminent domain to seize land for data centers
Power companies are using eminent domain to acquire land for the construction of data centers.
Big Tech Is Now Targeting Native American Land for Data Centers
Big Tech companies are targeting Native American lands for the placement of new data centers.
From Black Box to Executable Logic: Explainable Reinforcement Learning through Prolog Expert Systems
Researchers propose a method to transform deep reinforcement learning policies into readable and executable Prolog programs for better explainability.
A Critical Analysis of Trustworthy AI Tools, Mark Frameworks, and the Implementation Chasms
A critical analysis of trustworthy AI frameworks reveals a gap between high-level ethical guidelines and concrete implementation mechanisms.
Logic, Optimization, and Artificial Intelligence
This survey explores the synergy between logic and optimization in rule-based AI to improve transparency, explainability, and fairness.
SeerGuard: A Safety Framework for Mobile GUI Agents via World Model Prediction
SeerGuard is introduced as a safety framework for mobile GUI agents, utilizing a world model to predict and assess risks before actions are executed.
MGDT: MLLM-Guided Diffusion Transformer with Relation-Adaptive Mixture-of-Experts for Multimodal Knowledge Graph Completion
MGDT is a new framework for multimodal knowledge graph completion that uses an align-then-diffuse paradigm with MLLM guidance and Mixture-of-Experts.
Neuro-Symbolic AI for LEED compliance: Document-Centric Benchmarking, Deterministic Numeric Checking, and When Multimodal Hurts
A neuro-symbolic pipeline is tested for LEED compliance verification, finding that small local LLMs combined with deterministic numeric checkers can be effective.
ToolVerse: Unlocking Massive Environments and Long-Horizon Tasks for Agentic Reinforcement Learning
ToolVerse is a framework that scales agentic RL environments by integrating thousands of real-world tools via Model Context Protocols (MCPs).
S1-Omni: A Unified Multimodal Reasoning Model for Scientific Understanding, Prediction, and Generation
S1-Omni is presented as a unified multimodal reasoning model designed for scientific understanding, prediction, and generation across various domains.
Claude Fable produced a counterexample to the Jacobian Conjecture
Claude Fable AI successfully produced a counterexample to the Jacobian Conjecture, a long-standing problem in mathematics.
The Chickens and the Bulls (2012)
An article or discussion regarding 'The Chickens and the Bulls (2012)', likely a technical or mathematical puzzle/story.
GraphDx: A Cost-Aware Knowledge-Enhanced Multi-Agent Framework for Sequential Diagnosis
GraphDx is a multi-agent framework that uses Medical Diagnosis Knowledge Graphs to improve the accuracy and cost-efficiency of automated clinical diagnosis.