Image de couverture de livre

A First Proof Sprint

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Corneli, Joseph
Format:	Preprint
Publié:	2026
Sujets:	Artificial Intelligence Multiagent Systems 00A35, 68T30 I.2.4; I.2.6; K.3.2
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Enhancing Large Language Models through Neuro-Symbolic Integration and Ontological Reasoning
par: Vsevolodovna, Ruslan Idelfonso Magana, et autres
Publié: (2025)

Knowledge Equivalence in Digital Twins of Intelligent Systems
par: Zhang, Nan, et autres
Publié: (2022)

Causal Direction from Convergence Time: Faster Training in the True Causal Direction
par: Tamim, Abdulrahman
Publié: (2026)

Interpretation, Learning, and Empathy as One Constraint: A Residual-Adequacy Architecture with Accountable Abstention
par: Amornbunchornvej, Chainarong
Publié: (2026)

SALT-KG: A Benchmark for Semantics-Aware Learning on Enterprise Tables
par: Mulang, Isaiah Onando, et autres
Publié: (2026)

TrueReason: An Exemplar Personalised Learning System Integrating Reasoning with Foundational Models
par: Bulathwela, Sahan, et autres
Publié: (2025)

Emergent Formal Verification: How an Autonomous AI Ecosystem Independently Discovered SMT-Based Safety Across Six Domains
par: Untila, Octavian
Publié: (2026)

Uncovering Bugs in Formal Explainers: A Case Study with PyXAI
par: Huang, Xuanxiang, et autres
Publié: (2025)

Quantization Range Estimation for Convolutional Neural Networks
par: Yang, Bingtao, et autres
Publié: (2025)

Integrating Generative AI in Cybersecurity Education: Case Study Insights on Pedagogical Strategies, Critical Thinking, and Responsible AI Use
par: Elkhodr, Mahmoud, et autres
Publié: (2025)

Understanding the Uncertainty of LLM Explanations: A Perspective Based on Reasoning Topology
par: Da, Longchao, et autres
Publié: (2025)

AdaptOrch: Task-Adaptive Multi-Agent Orchestration in the Era of LLM Performance Convergence
par: Yu, Geunbin
Publié: (2026)

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach
par: Chen, Xin, et autres
Publié: (2024)

Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
par: Chen, Tiejin, et autres
Publié: (2026)

T-Norm Operators for EU AI Act Compliance Classification: An Empirical Comparison of Lukasiewicz, Product, and Gödel Semantics in a Neuro-Symbolic Reasoning System
par: Laabs, Adam
Publié: (2026)

Intersymbolic AI: Interlinking Symbolic AI and Subsymbolic AI
par: Platzer, André
Publié: (2024)

From Safety Risk to Design Principle: Peer-Preservation in Multi-Agent LLM Systems and Its Implications for Orchestrated Democratic Discourse Analysis
par: Dietrich, Juergen
Publié: (2026)

High Quality Embeddings for Horn Logic Reasoning
par: Zhang, Yifan, et autres
Publié: (2026)

Policy Cards: Machine-Readable Runtime Governance for Autonomous AI Agents
par: Mavračić, Juraj
Publié: (2025)

Conversational No-code, Multi-agentic Disease Module Identification and Drug Repurposing Prediction with ChatDRex
par: Süwer, Simon, et autres
Publié: (2025)

A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making
par: Núñez-Molina, Carlos, et autres
Publié: (2023)

Formal Proofs as Structured Explanations: Proposing Several Tasks on Explainable Natural Language Inference
par: Abzianidze, Lasha
Publié: (2023)

LLM-FACETS: A Privacy-Preserving Framework for Evaluating LLM Transparency and Accountability
par: Lucas, Tom, et autres
Publié: (2026)

Modelling Human Values for AI Reasoning
par: Osman, Nardine, et autres
Publié: (2024)

A Domain-Independent Agent Architecture for Adaptive Operation in Evolving Open Worlds
par: Mohan, Shiwali, et autres
Publié: (2023)

Demand-Driven Context: A Methodology for Building Enterprise Knowledge Bases Through Agent Failure
par: Navakoti, Raj, et autres
Publié: (2026)

Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning
par: Raichur, Nisha L., et autres
Publié: (2024)

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure
par: Bottino, Federico, et autres
Publié: (2026)

ARCADIA: Scalable Causal Discovery for Corporate Bankruptcy Analysis Using Agentic AI
par: Maturo, Fabrizio, et autres
Publié: (2025)

Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning
par: Chanda, Prateek, et autres
Publié: (2025)

Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation
par: Gharami, Kanchon, et autres
Publié: (2025)

Yanasse: Finding New Proofs from Deep Vision's Analogies, Part 1
par: Linhares, Alexandre
Publié: (2026)

AI Mother Tongue: Self-Emergent Communication in MARL via Endogenous Symbol Systems
par: Liu, Hung Ming
Publié: (2025)

Adaptive Trust Consensus for Blockchain IoT: Comparing RL, DRL, and MARL Against Naive, Collusive, Adaptive, Byzantine, and Sleeper Attacks
par: Padia, Soham, et autres
Publié: (2025)

BigBang-Proton Technical Report: Next-Word-Prediction is Scientific Multitask Learner
par: Wu, Hengkui, et autres
Publié: (2025)

Navigational Thinking as an Emerging Paradigm of Computer Science in the Age of Generative AI
par: Levin, Ilya
Publié: (2026)

Improving Graph Embeddings in Machine Learning Using Knowledge Completion with Validation in a Case Study on COVID-19 Spread
par: Napoli, Rosario, et autres
Publié: (2025)

Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution
par: Liu, Xiaoou, et autres
Publié: (2026)

Modularity in Transformers: Investigating Neuron Separability & Specialization
par: Pochinkov, Nicholas, et autres
Publié: (2024)

When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges
par: Darshan, Parth, et autres
Publié: (2026)