All Articles
17660 articles total
EgoSafetyBench: A Diagnostic Egocentric Video Benchmark for Evaluating Embodied VLMs as Runtime Safety Guards
Introduction of EgoSafetyBench, a diagnostic egocentric video benchmark designed to evaluate Vision-Language Models (VLMs) as runtime safety guards for embodied AI.
A Category Theory Account of AI Identity
A category-theoretic formalization of AI identity, providing a structured hierarchy of criteria to determine when an AI system remains the same over time and deployments.
Adaptive Perturbation Selection for Contrastive Audio Decoding
Explores adaptive perturbation selection for contrastive audio decoding in Large Audio-Language Models (LALMs) to reduce hallucinations.
Leveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring
Presents UPADNet, an unrolled network that uses amplitude and phase decomposition to improve image deblurring, especially in high-noise environments.
Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification
Introduces a particle-based diversification framework for Test-Time Adaptation (TTA) to mitigate underspecification and improve model robustness under distribution shifts.
Validating Causal Abstraction Metrics on Simulated Complex Systems
Introduces the Causal Abstraction Error (CAE), a continuous validity metric for discovering and validating high-level causal explanations of complex systems.
ASPIRE: Agentic /Skills Discovery for Robotics
Presents ASPIRE, a continual learning system for robotics that autonomously writes and refines control programs using a code-as-policy paradigm.
SEFORA: Student Essays with Feedback Corpus and LLM Feedback Evaluation Framework
Introduces SEFORA, a public corpus of student essays with instructor feedback, and UniMatch, an evaluation framework for LLM-generated writing feedback.
Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning
Proposes entropy-regularized probabilistic gates to maintain uncertainty in sparse federated optimization, improving generalization in data-scarce federated learning.
We Don't Have to Be This Bad at Improving Society
A discussion about the societal shortcomings in improving human conditions and systemic failures.
The Fall of the Theorem Economy
An exploration of the 'Theorem Economy' and the shifting nature of mathematical proof and value.
Google loses fight over record $4.7B EU antitrust fine
Google loses a legal battle regarding a massive EU antitrust fine of $4.7 billion.
My Favorite Keyboards
A user shares their personal preferences and recommendations for various computer keyboards.
GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity
A research paper proving that GRPO, Dr. GRPO, and DAPO are variations of a single mathematical identity based on group standard deviation.
EVOTS: Evolutionary Transformer Search for Time Series Forecasting
Introduction of EVOTS, an evolutionary neural architecture search framework for optimizing Transformer models for time-series forecasting.
Scaling Up Thermodynamic AI Models
Research on scaling thermodynamic AI models using backpropagation-based algorithms for training on Ising machine hardware.
Play Like Champions: Counterfactual Feedback Generation in Latent Space
A framework for generating counterfactual feedback in latent space to help human players improve at real-time strategy games like StarCraft II.
HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems
HydraCollab is an adaptive collaborative-perception framework for distributed autonomous systems that optimizes bandwidth and accuracy.
SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing
Introduction of SLIM-RL, a risk-budgeted random-masking RL method that improves training efficiency for diffusion LLMs.
Enhancing Oracle Bone Inscription Recognition via Multi-Scale Layer Attention
Researchers propose Multi-Scale Layer Attention (MSLA) to improve the recognition of ancient Chinese Oracle Bone Inscriptions by modeling multi-scale and cross-layer feature interactions.