All Articles
17168 articles total
Knowledge-Based Design Requirements for Generative Social Robots in Higher Education
Research on knowledge-based design requirements for generative social robots used as tutors in higher education.
Control the Ideas, Not the Code
A discussion on the philosophy of controlling ideas rather than the specific implementation of code.
The 'absolute magic' of Morse code that still connects people globally
An exploration of the enduring utility and 'magic' of Morse code in global communication.
AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders
Introduces AutoGraphAD, an unsupervised anomaly detection method for networks using Heterogeneous Variational Graph Autoencoders.
Point of Order: Action-Aware LLM Persona Modeling for Data-Grounded Civic Deliberation
Presents a pipeline for converting Zoom recordings into speaker-attributed transcripts to improve LLM persona modeling for civic deliberation simulations.
RIS-Assisted Downlink Pinching-Antenna Systems: GNN-Enabled Optimization Approaches
Proposes a GNN-enabled optimization approach for RIS-assisted pinching-antenna systems to maximize sum rate and energy efficiency in wireless communications.
Data-Driven Learnability Transition of Measurement-Induced Entanglement
Uses neural networks in a self-supervised manner to detect measurement-induced entanglement in quantum systems, identifying a computational learnability transition.
How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy
A practical guide on generating synthetic data using Differential Privacy (DP) to protect user privacy while maintaining data utility for AI.
ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning
Introduces ReinforceGen, a hybrid system combining imitation learning and reinforcement learning for long-horizon robotic manipulation.
Transition Matching Distillation for Fast Video Generation
Presents Transition Matching Distillation (TMD) to distill video diffusion models into efficient few-step generators for faster video generation.
Principles of Lipschitz continuity in neural networks
A theoretical examination of Lipschitz continuity in neural networks and its role in robustness, generalization, and frequency signal propagation.
Show HN: DOM-docx – HTML to native, editable Word docs (MIT)
DOM-docx is a tool that converts HTML content into native, editable Microsoft Word documents under the MIT license.
Leak of San Francisco Police Drone Footage Exposes Reality of Urban Surveillance
Leaked drone footage from the San Francisco Police Department reveals the extent of urban surveillance practices.
Uber’s robotaxi lobbying effort puts it on a collision course with Waymo
Uber and Waymo are engaged in conflicting lobbying efforts in Washington D.C. regarding robotaxi regulations.
Single-Frame Point-Pixel Registration via Supervised Cross-Modal Feature Matching
A new detector-free framework for single-frame point-pixel registration improves LiDAR and camera matching in autonomous driving.
GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs
GrAInS is introduced as a gradient-based attribution method for inference-time steering of LLMs and VLMs to improve alignment and reduce hallucinations.
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Research indicates that Retrieval-Augmented Generation (RAG) is more token-efficient and effective than long-context prompting for clinical reasoning over EHRs.
REAL: REtrieval-reAsoning and Logic-constructed Attention Behaviors for Long-Context KV Cache Compression
REAL is a new KV cache eviction method that uses multi-behavior analysis to significantly compress memory requirements for long-context LLMs.
Contrastive Weak-to-strong Generalization
Contrastive Weak-to-Strong Generalization (ConG) leverages contrastive decoding to improve the transfer of capabilities from weak to strong LLMs.
Explaining Human Choice Probabilities with Simple Vector Representations
A study uses simple vector representations to explain human choice probabilities in stochastic hide-and-seek tasks.