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JADR protocol uses Jacobian space analysis to measure models' internal danger-recognition representations, bypassing LLM-judge evaluation artifacts in jailbreak robustness testing.
Spotify is rolling out a new AI-powered conversational feature that lets Premium subscribers chat with the app to discover music, podcasts, and audiobooks, and more.
Also covered by The Verge AI
Framework evolves evaluation metrics alongside agent skills using evolutionary search over drawback detectors, enabling self-improving systems without pre-defined oracles.
Adaptive Vector-Quantized Attention allocates codebook capacity proportionally to attention importance, reducing transformer complexity from O(N²) to O(MN) with precision targeting.
Study questions whether multimodal emotion recognition requires >1B parameters, testing compression of 7B+ models for real-time deployment on edge devices.
OpenAI has spent the better part of the year involved in lawsuit after lawsuit, including one from the world's richest man. But last Friday, the company was hit with one of the highest-profile legal actions yet - from Apple. OpenAI's expensive hardware bet is what's on the…
Superhuman’s latest AI email drafting feature is its most convincing yet, generating replies that often required little to no editing in our testing.
Directional constraints improve exploration efficiency in safe reinforcement learning for robotics, balancing safety guarantees with task performance in constrained optimization.
Encoder-decoder transformer optimizes quantum circuits for fault-tolerant computing by minimizing T gates while maintaining functional equivalence.
Learning-accelerated ADMM algorithm accelerates scenario-based model predictive control for real-time planning via parallel computing and Moreau envelope learning.
Multi-task facial emotion recognition system for ABAW challenge using frozen lightweight extractors with temporal smoothing and ensemble fusion.
LLMs fine-tuned to predict chemical reaction mechanisms step-by-step, reducing hallucinations versus name-reaction prediction approaches.
Analysis of length bias in multiple-choice benchmarks shows length normalization over-corrects; proposes Bayesian alternative scoring for fairer ranking.
Constraint-aware federated RL aggregation method for microgrid energy coordination that prevents unsafe global behavior via penalty-based weighting.
Philosophical analysis of deploying opaque AI systems, examining user judgment, virtue, and autonomy-opacity tradeoffs in safety and control.
While recent advances in 3D generation have enabled impressive visual synthesis, existing methods often rely on 2D diffusion supervision without explicit mechanisms for geometric consistency, leading to spatial hallucinations such as duplicated structures and misaligned…
Farm site discovery from satellite imagery is a spatiotemporal candidate ranking problem because farm evidence is distributed across pasture, field boundaries, roads, buildings, and seasonal vegetation patterns. Direct farm labels are often incomplete, which makes fully…
Failure attribution for LLM-based agentic systems, i.e., identifying which steps in a failure trajectory caused the task to fail, is critical for debugging and improving these systems. Existing approaches either rely on prompting-based pipelines, which are computationally…
ESFP benchmark measures whether LLMs distinguish and coherently shift between neutral attribution and self-stance epistemic registers in contested claims.
Empirical study of 188 grokking runs shows representational priors must match task-relevant feature families to enable generalization; label-free invariance priors work via commutation symmetry.
Elenchos framework evaluates abductive reasoning in LLMs via formal-system mutation detection, exposing gap between pattern recognition and latent-hypothesis inference.
Probabilistic load forecasting framework for smart buildings handles input uncertainty via reconstruction and calibration of prediction intervals.
Anthropic pledges $10M to Canadian AI research initiatives, expanding regional R&D presence.
XGBoost emulation of high-dimensional likelihood functions in physics and cosmology improves efficiency over traditional global fits.
Bulkhead automates detection and remediation of container path-traversal vulnerabilities exacerbated by AI workload resource sharing (GPUs, agent workspaces).
FileMark VSCode extension uses line-anchored feedback to reduce token generation in Claude Opus (22%) and Sonnet (58%), cutting code-editing latency and cost.
Neuro-symbolic approach integrates MaxSAT constraint reasoning into vision-language models to enforce logical consistency in Sudoku solving.
Label-decoupled style augmentation improves domain generalization in multi-label remote-sensing classification by avoiding per-class contamination.
Cost-aware speculative decoding for Mixture-of-Experts LLMs optimizes expert activation patterns to reduce inference cost beyond token acceptance alone.
CARE-PPO combines PPO fine-tuning with loss prediction to jointly train LLMs for accurate numerical estimates and calibrated confidence signals in quantitative prediction tasks.