Safety & Evaluation

A
Showing 1–30 of 71
  • IEEE Spectrum (AI section) · EN Safety & Evaluation
    Guarding the Gates of Knowledge
    IEEE Spectrum editor on AI-faked papers and publishers' gatekeeping struggle
    Claude Gemini GPT Software Engineering
    The author argues AI answers still can't be trusted, so users must verify. Applied at scale, that maxim challenges publishers guarding the scientific record of peer-reviewed work. A feature on faking a paper with AI shows the human gatekeepers trying to hold the line.
    Read original (IEEE Spectrum (AI section)) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    GhostPrefix: Synchronization-Free Universal Prefix Attacks for ASR Manipulation
    Retrieval-Augmented Generation (RAG) Speech Processing
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Multimodal
    Aligning MLLMs with the Latent Structure of Human Cognition via Behavior-Derived Semantic Dimensions
    Embeddings Machine Learning Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    ReX-GG: a LLM Ensemble Pipeline for Relation-extraction and Graph Generation
    Machine Learning Neural Network Retrieval-Augmented Generation (RAG) Software Engineering
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    Iterated Integrals as Lexical Fingerprints: Path Signature Embeddings for Lexical Similarity
    Embeddings Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning Transformer
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • 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
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • 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)
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • 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.CL (Computation and Language) · EN New Model Releases
    Peeling the Matryoshka: Extracting Ontological Structure from Retrieval Embeddings
    Embeddings Neural Network Natural Language Processing (NLP) Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • 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 Inference & Efficiency
    When Steering Shifts Discourse: Identifying and Intervening on Discourse-Level Changes due to Activation Steering in LLMs
    Inference
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Training & Fine-tuning
    KV-Cache Patching: Tracing How and Where Fine-Tuned Behaviors Arise
    Fine-tuning Software Engineering
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • OpenAI Blog · EN Safety & Evaluation
    Community safety report and new protections for teens
    OpenAI expands ChatGPT violence prevention, adds protections for teens
    GPT OpenAI Reinforcement Learning
    OpenAI says it is strengthening violence prevention in ChatGPT with expanded safeguards and earlier interventions, along with a new commitment to public safety reporting. The post's title also points to new protections for teens.
    Read original (OpenAI Blog) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    A prospective randomized study of patient-centered AI for clinical visit preparation
    Google
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    ShallowDefend: Harnessing Shallow Safety Alignment for Multi-Turn Defender
    Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    How I Aligned Your Model: Scaling Up Multilingual Safety Training with Templates
    Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.CL (Computation and Language) · EN Safety & Evaluation
    A Low-Rank Space Captures Linear Alignment Between LLM and Human Neural Activity During Naturalistic Language Listening
    Embeddings Machine Learning Neural Network
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    Training language models in simulation for psychiatric intake
    Neural Network Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • OpenAI Blog · EN Safety & Evaluation
    An updated Model Spec for more capable and beneficial AI
    OpenAI updates Model Spec with five core values for capable AI
    OpenAI
    OpenAI published an updated Model Spec describing five core values meant to guide more capable AI toward sound judgment, respect for human agency, and faithfulness to human intent.
    Read original (OpenAI Blog) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    SCARL: Sequence Confidence-Aligned Reinforcement Learning
    Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    The Athlete as a Scientist of One: Agentic Bayesian Experimental Design for Individualized Physiology from Consumer Wearables
    AI Agents
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Training & Fine-tuning
    Latent Prediction Yields Cross-Subject Alignable Representations in Sensory-Evoked fMRI
    Embeddings Fine-tuning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • arXiv cs.AI (Artificial Intelligence) · EN Safety & Evaluation
    Learned Terminal Costs for Short-Horizon Model Predictive Control of Autonomous Trucks in Interactive Highway Traffic
    Reinforcement Learning
    Read original (arXiv cs.AI (Artificial Intelligence)) ↗
  • Data Center Dynamics · EN Safety & Evaluation
    Simplifying safety to drive savings
    Simplifying safety to drive savings: Fastenal's consolidation
    Article on how Fastenal used consolidation to standardize data center spend, simplifying safety purchasing to drive savings.
    Read original (Data Center Dynamics) ↗
  • Stratechery (free posts) · EN Safety & Evaluation
    An Interview with Palantir CTO Shyam Sankar About the AI Religious War
    Stratechery interviews Palantir CTO Shyam Sankar on the AI 'religious war'
    Stratechery interviews Palantir CTO Shyam Sankar about AI diffusion and safety, the role of forward-deployed engineers, and what the battle in tech is actually about, framed in the title as an AI 'religious war'.
    Read original (Stratechery (free posts)) ↗
  • OpenAI Blog · EN Safety & Evaluation
    How we detect frontier model misalignment
    OpenAI details layered monitoring for frontier model misalignment
    OpenAI
    OpenAI describes how it uses layered monitoring to detect misalignment in frontier models and unauthorized agent behavior, so responders can step in before incidents escalate.
    Read original (OpenAI Blog) ↗
  • arXiv cs.LG (Machine Learning) · EN Training & Fine-tuning
    Safe Multi-Objective Reinforcement Learning: Zero Constraint Violation and Primal-Averaging Convergence
    Algorithms & Theory Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    More Is Better? Exploring Latent Correspondence in Federated Hypergraph Learning
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    IMRouter: Imbalance-aware Temporal Pattern Routing for LLM-based Time Series Forecasting
    Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗