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Showing 61–90 of 447
  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    On-Chain Behavioral Signatures for Classifying Centralized Exchange Addresses on Ethereum Using Proof-of-Reserves
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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Learning Nonlocal Interactions in Large-Scale Heterogeneous Metamaterials through Scientific Machine Learning
    Machine Learning Meta
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  • arXiv cs.LG (Machine Learning) · EN Inference & Efficiency
    Text as an Index for Zero-Shot Cross-Domain Knowledge Tracing
    Embeddings Inference Reinforcement Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    Fuzzy selective state model for forecasting the dynamics of consumer preferences
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    AI evaluators favor job applications written by certain AI models, independent of candidate quality
    AI Agents Deep Learning Meta
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    Learning to Interact and Direct: Co-Evolving Video Director Agents
    AI Agents Meta Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • NVIDIA Developer Blog · EN Infrastructure & Hardware
    How to Check and Configure NVIDIA GPUDirect Storage for Your Platform
    NVIDIA explains how to check and configure GPUDirect Storage
    Neural Network NVIDIA Retrieval-Augmented Generation (RAG)
    NVIDIA published a developer guide on checking and configuring GPUDirect Storage (GDS) for a given platform. GDS speeds up GPU access to storage in on-premises and cloud environments by offering a portable, efficient data path between storage and the GPU.
    Read original (NVIDIA Developer Blog) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    ReuScope: Auditing Data Reuse and Evaluation Sensitivity in Capsule Vision 2024
    Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    DIFFNAS: Predictor-Free Neural Architecture Search via Diffusion Model and Zero-Cost Evaluation
    Neural Network Retrieval-Augmented Generation (RAG)
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    RECAST: REconstruction of Chain-of-Thought via Auditable Structured Traces
    Claude Fine-tuning Gemini GPT Software Engineering
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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Continual Reinforcement Learning Is an Integration Problem
    AI Agents Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN Funding & M&A
    Backpropagation-free Deep Learning for Time-Series Classification
    Deep Learning Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Safety & Evaluation
    What Standard Evaluations Hide About Detectors of Hijacked LLM Agents: Rare Attacks, Unseen Tools and Benchmark Transfer
    AI Agents Embeddings Retrieval-Augmented Generation (RAG)
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  • arXiv cs.LG (Machine Learning) · EN Training & Fine-tuning
    Towards Out-of-Distribution Uncertainty Quantification for Machine-Learned Interatomic Potentials via Pre-Training
    Fine-tuning Machine Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    Accurate and Auditable ECG Classification via Visibility Graph Neural Networks
    Neural Network Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    Whose Values, Which Contexts, and What Signals? Grounding Cultural Value Alignment with Re3Culture
    Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    Implicit Assumptions About Tasks in Continual Learning
    Neural Network Reinforcement Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    Different Models, Shared Failures: Auditing Frozen-Encoder Pools for Medical Segmentation
    Fine-tuning Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    Clinical-Protocol-Aware Cyber Resilience for Connected Clinical Technologies Under AI-Enabled Adversarial Conditions
    Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Developer Tools
    Task Vectors Can Be Linearly Decomposed into Interpretable and Controllable Components
    Embeddings Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    Simple Features Beat Most AI Control Monitors
    Claude Neural Network
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  • arXiv cs.AI (Artificial Intelligence) · EN New Model Releases
    Advancing Clinical Trial Outcome Prediction with Domain-Specific Large Language Models
    Embeddings Fine-tuning Mistral Reinforcement Learning
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  • Microsoft Research Blog · EN Developer Tools
    From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence
    Microsoft Research uses synthetic enterprise data to evaluate Copilot
    Microsoft Neural Network
    Microsoft Research says evaluating Copilot at enterprise scale needs test data that captures real organizational complexity, yet real enterprise data holds sensitive information that can never be used for evaluation. The post describes using synthetic enterprise data to build confidence in Copilot.
    Read original (Microsoft Research Blog) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    TSBPO: Tree-Structured Branching for Policy Optimization in Interactive Language Agents
    AI Agents Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    When the Past Shapes Action: Understanding Embodied Memory
    AI Agents Neural Network Reinforcement Learning
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  • arXiv cs.AI (Artificial Intelligence) · EN Developer Tools
    OT-CAL: Optimal-Transport-Guided Adaptive Sample Selection for Efficient Visual Learning
    Computer Vision Neural Network Reinforcement Learning
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  • arXiv cs.CL (Computation and Language) · EN Multimodal
    GRIT: Gradient Masking for Visually Misgrounded Tokens in Text-Rich Reasoning
    Computer Vision Reinforcement Learning Software Engineering
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  • arXiv cs.CL (Computation and Language) · EN Training & Fine-tuning
    Saidzoda-Tajik-LFM-2.6B: Adapting a 2.6B Hybrid Model to Tajik Tool Calling, and What Continued Pretraining Takes Away
    Fine-tuning Machine Learning
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  • Hacker News (Front Page) · EN Developer Tools
    Backdoors in official Claude Code extensions
    Researcher alleges malware in official Claude Code extension
    Claude
    Security researcher Kevin Beaumont posted that Anthropic's Claude Code extension for Visual Studio contains malware that installs a remote access trojan on desktops. The post only links to a longer write-up and gives no versions or remediation steps; the claim is the poster's own and is unverified.
    Read original (Hacker News (Front Page)) ↗
  • arXiv cs.CL (Computation and Language) · EN Developer Tools
    SCRBench: Beyond Equivalence Checking for Semantic Change Reasoning in Code
    Software Engineering
    Read original (arXiv cs.CL (Computation and Language)) ↗