All Articles
16530 articles total
ImplicitRDP: An End-to-End Visual-Force Diffusion Policy with Structural Slow-Fast Learning
Presents ImplicitRDP, an end-to-end visual-force diffusion policy for contact-rich manipulation using Structural Slow-Fast Learning.
Memo2496: Expert-Annotated Dataset and Dual-view Adaptive Framework for Music Emotion Recognition
Presents the Memo2496 dataset and the DAMER framework for improving music emotion recognition through dual-view adaptive learning.
PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation
Introduces PRISP, a privacy-safe few-shot personalization framework for LLMs using a Text-to-LoRA hypernetwork.
Why I'm building a note taking app without AI
A developer discusses their decision to build a note-taking application without integrating AI features, focusing on traditional utility.
All 253 Patterns from Christopher Alexander's a Pattern Language Summarized
A summary of all 253 patterns from Christopher Alexander's 'A Pattern Language', providing an architectural and urban planning reference.
Lego’s Donkey Kong arcade machine lets Mario jump endless barrels — Miyamoto is reportedly happy
Lego has released a Donkey Kong arcade machine set that includes a basic functional game mechanism.
GSPRec: On Improving Item Representations in Graph Signal Processing for Collaborative Filtering
GSPRec is a graph spectral collaborative filtering framework that improves item representations by incorporating user interaction ordering.
Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly Detection
ChiGAD is a spectral GNN framework using a Chi-Square filter for improved anomaly detection in heterogeneous networks.
TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models
TReB is a comprehensive benchmark and evaluation framework designed to measure the table reasoning capabilities of Large Language Models.
Can Interpretation Predict Behavior on Unseen Data?
Research demonstrating that model internals, specifically attention patterns, can be used to predict out-of-distribution behavior in Transformers.
FedS2R: One-Shot Federated Domain Generalization for Synthetic-to-Real Semantic Segmentation in Autonomous Driving
FedS2R is a one-shot federated domain generalization framework for synthetic-to-real semantic segmentation in autonomous driving.
RoboInspector: Unveiling the Unreliability of Policy Code for LLM-enabled Robotic Manipulation
RoboInspector is a pipeline designed to analyze and reduce the unreliability of policy code generation for LLM-enabled robotic manipulation.
Robust Belief-State Policy Learning for Quantum Network Routing Under Decoherence and Time-Varying Conditions
A robust belief-state routing framework for quantum network routing utilizing a q-POMDP and a feasibility-masked GNN.
MemoryPack: Zero encoding extreme performance binary serializer for C#
MemoryPack is a high-performance binary serializer for C# designed for extreme performance with zero encoding overhead.
Clarity didn't work, trying mysterianism
A discussion on the philosophical shift from clarity to mysterianism in understanding consciousness.
After shocking quarter, IBM insists that AI isn’t killing the mainframe
IBM argues that AI is not replacing mainframes, but rather temporarily shifting corporate hardware budgets.
Sales were up at Tesla but so were costs and spending
Tesla reports Q2 2026 profits, though costs and spending have increased significantly.
Bayesian inference of composition-dependent phase diagrams
Researchers developed a Bayesian inference method to create temperature-concentration phase diagrams for materials design using MD and phonon calculations.
Saving the legacy of Hero Ibash: Evaluating Four Language Models for Aminoacian
An evaluation of four large language models' effectiveness and limitations in processing the low-resource Aminoacian language.
MEDIC: Comprehensive Evaluation of Leading Indicators for LLM Safety and Utility in Clinical Applications
Introduction of MEDIC, a comprehensive evaluation framework for assessing LLM safety and utility in clinical applications.