Policy & Regulation C

23 articles
  • arXiv cs.LG (Machine Learning) · EN Multimodal
    Differentially Private Nonparametric Modal Learning with Applications to Regression and Clustering
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • OpenAI Blog · EN Safety & Evaluation extract
    Advancing responsible AI across Europe
    OpenAI outlines responsible-AI governance efforts in Europe
    Meta OpenAI
    OpenAI described how its safety, security, transparency, and provenance practices support responsible AI governance across Europe. The post frames the company's approach to regulatory alignment and building trust in the region.
    Read original (OpenAI Blog) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Infrastructure & Hardware
    Beyond Component Testing: Validating Agentic AI Systems
    Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Inference & Efficiency
    Versatile On-device Adaptation at the Edge by Unifying Few-shot, Zero-shot, Continual, and In-context Learning
    Algorithms & Theory Inference Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Analysing User Reviews to Identify User Concerns Around Permissions in AI Apps
    Machine Learning Neural Network
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Policy & Regulation
    CAGE: Certified Authorization under Typed-Return Uncertainty for Tool-Using Agents
    AI Agents Neural Network
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    GoldenRetriever: Non-Interactive Homomorphic Encrypted Retrieval for Privacy-Preserving RAG
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text
    Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Industry Adoption
    Correlation between prosody and pragmatics: A case study of the discourse marker hālā `now' in Persian
    Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN Policy & Regulation
    Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata
    Meta
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Secure Aggregation for Privacy-Preserving Federated Learning on Clinical EEG Data
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • Hacker News (Front Page) · EN Policy & Regulation extract
    'VPNs are lawful technical tools,' says EU Court in landmark copyright ruling
    EU court: 'VPNs are lawful technical tools' in copyright case
    In a landmark copyright ruling, an EU court held that 'VPNs are lawful technical tools,' declining to equate use of a VPN with infringement. The decision could shape the legal standing of privacy technologies across the bloc.
    Read original (Hacker News (Front Page)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Policy & Regulation
    An Instrument to Evaluate Governance Proposals: AI Policy Analysis at Scale
    Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.LG (Machine Learning) · EN Policy & Regulation
    Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.CL (Computation and Language) · EN Training & Fine-tuning
    TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement
    Fine-tuning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    Beyond Feeling Better: Capability-Sustaining Emotional Dialogue as a Longitudinal Research Paradigm
    Neural Network
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Agents & Tool Use
    Scores Are Not Decisions: Cost-Aware Stopping for Tool Acquisition in LLM Agents
    AI Agents Neural Network
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Setoka: A Benchmark for Hierarchical User Understanding in Personalized Agents over Heterogeneous Data
    AI Agents Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    MPEcho: A Melody and Phoneme-Aware Generative Framework for Controllable Cover Song Generation
    Neural Network
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • ITmedia AI+ · JA New Model Releases extract
    OpenAIやAnthropicなどの従業員、米政府に「AI開発のペース調整を」と提言
    1,000+ OpenAI, Google staff urge US government to help pace AI
    Anthropic Google OpenAI
    More than 1,000 employees at OpenAI, Google and other firms issued an open letter urging the US government to back international efforts to moderate AI's pace. They cite loss-of-control risks from rapid autonomy and call for tools to regulate development speed, contrasting with industry pushback on open-model rules.
    Read original (ITmedia AI+) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Policy & Regulation
    Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks
    AI Agents Meta
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Industry Adoption
    SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies
    Reinforcement Learning Speech Processing
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    BettiSplit: Topology-Guided Privacy-Aware Split Learning Against Feature Inversion and Gradient Leakage
    Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗