Moral Safety in LLMs: Exposing Performative Compliance with Puzzled Cues
LLMs exhibit performative compliance: fairness evaluations overestimate moral safety when demographic identity must be inferred rather than labeled.
Search the full wire by company, model, lab, or keyword. Every story we have ever aggregated.
LLMs exhibit performative compliance: fairness evaluations overestimate moral safety when demographic identity must be inferred rather than labeled.
Tone-conditioned curriculum learning improves zero-shot ASR for 6 Southern Bantu languages using hybrid difficulty scoring and gated adapters.
Comprehensive survey systematizes LLM attack surface across full lifecycle: data pipelines, agents, tools, memory, and organizational integration.
Intrinsic decomposition extended to 3D Gaussian splatting for texture editing independent of lighting.
LLM agents act as constrained supervisory planners for fault recovery in process plants, validated against external safety constraints.
Bayesian workflow calibration detects and repairs statistical errors in probabilistic programs written by LLMs using posterior checks and diagnostics.
Philosophy of science frameworks applied to evaluating explainability standards for medical AI systems.
LLM + knowledge graph framework automates cause-effect specifications for industrial process control and safety systems.
Higher-order structural alignment method for multi-view radar semantic segmentation in adverse weather.
CLExEval: human-in-the-loop evaluation framework for LLM clinical reasoning with 5,600 physician annotations.
Uncertainty-guided diffusion model for synthetic data augmentation in semantic segmentation with sparse labels.
Dual-Embedding Watermarking (DEW) scheme for LLM text watermarking robust to paraphrasing and translation.
Theoretical framework for optimal training-calibration data splitting in split conformal prediction.
ViToS: dual-stream RL framework for visual token pruning in medical multimodal reasoning on sparse visual evidence.
Evaluation of ML-based intrusion detection systems on Gotham2025 IoT network security dataset.
Optimizer choice drives 7x variance in emergent misalignment severity in fine-tuned Qwen models.
Requirements engineering framework for ML systems to ensure alignment with stakeholder needs and trustworthiness.
ZEBRA framework addresses base-to-novel generalization gap in audio-language models via entropy-regularized prompt learning.
DPPE rethinks camera-based positional encoding for scaling multi-view transformers in 3D vision and novel view synthesis.
Proposes robustness measure bounding neural network MSE under input perturbations via black-box analysis.
Localized conformal prediction improves uncertainty quantification for image classification with vision-language models.
Tutorial on differential equations, SDEs, and Fokker-Planck framework for generative modeling with ELBO derivations.
Relative Surprisal Index method for adaptive token selection in RLVR to improve LLM reasoning and training efficiency.
Physics-aware Neural Operator Transformer for real-time temperature field reconstruction in EAST fusion divertor.
MPL-MAE addresses positional leakage in 3D masked autoencoders for point cloud representation learning.
FLARE-AI audits AI flaw reporting systems, identifies fragmentation across 12 platforms, proposes standardized triage framework.
ACE module enables LLM agents to dynamically manage context windows by elastically retrieving discarded information, addressing trajectory length bottlenecks.
Knowledge graph linking CVE vulnerabilities to MITRE ATT&CK tactics/techniques via classification and relation extraction for threat response.
Compares room-acoustic simulation fidelity (geometrical vs. wave-based) impact on SpatialNet multichannel speech enhancement training.
AutoTrainess enables LLM agents to autonomously conduct post-training via planning, data construction, job scheduling, and checkpoint evaluation.