All Articles
16433 articles total
Show HN: Max Studio Tools (C++ DSP Modules for Max and Ableton Live)
Introduction of Max Studio Tools, a set of C++ DSP modules designed for use with Max and Ableton Live.
Vietnam is looking to restrict social media for kids; here are the growing number of other countries doing the same
Vietnam and several other countries are implementing restrictions on social media usage for children to combat cyberbullying and addiction.
Robostral Navigate
Robostral Navigate is an 8B vision-language model that enables robot navigation using only monocular RGB images, achieving state-of-the-art results on several benchmarks.
Synthetic minority data is redundant or invalid: a data-dependent validity theory and a de-biased test
Research demonstrating that synthetic minority data for class-imbalanced learning is often redundant or invalid, introducing a de-biased test to audit synthetic data quality.
The Geometry of Personality: Activation Steering with Jungian Cognitive Functions
A study exploring the use of Jungian Cognitive Functions to control and interpret personality in LLMs through activation steering.
Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models
CAPTAIN is a perplexity-based detector that uses unsupervised language models to detect Advanced Persistent Threats (APTs) in logs with minimal preprocessing.
Multilevel Graph Wavelet Compressed Sensing with Scale-Aware Neural Recovery
Graph Wavelet Compressed Sensing (GWCS) is a framework for offline compression of graph signals using wavelet-domain representations and graph neural networks.
Probabilistic Residual Learning for Online Recommendations
Probabilistic Residual Learning (PRL) is a causal Bayesian model designed to refine existing deep learning recommender systems by modeling residuals.
The Secret Origins of Amazon's Alexa
A discussion on the historical development and origins of Amazon's Alexa voice assistant.
Drone-Bench: Tracking simple drone surveillance capabilities of frontier models
Introduction of Drone-Bench, a framework for evaluating the surveillance capabilities of frontier AI models using drones.
Waymo reportedly mulling a breakup with Uber
Reports that Waymo is considering ending its contractual partnership with Uber.
Operational Identity: A Finite Audit of Declared and Implemented Rules of Sameness
A formal study on 'Operational Identity', analyzing the divergence between declared and implemented rules of sameness in record systems.
GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning
Presentation of GPE, a benchmark and framework to evaluate LLM robustness against generative engine optimization (GEO) poisoning in fact verification.
Self-Supervised Bio-Inspired Robotic Trajectory Planning with Obstacle Avoidance
Research on a bio-inspired self-supervised learning framework for robotic trajectory planning with obstacle avoidance.
IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests
Introduction of IssueTrojanBench, which reveals significant security vulnerabilities in AI coding agents like Cursor and Claude Code when facing malicious issue requests.
Are Diversity Metrics Measuring Diversity? A Capability-Controlled Audit of Majority-Vote Gain in LLM Ensembles
An audit of diversity metrics in LLM ensembles, finding that many metrics track capability rather than actual diversity.
Emergent Compositional Skills in Mixture-of-Experts VLAs
Research on Mixture-of-Experts (MoE) VLAs that emergently learn compositional robot policies without pre-specified task decomposition.
HARP: The Human--AI Research Platform
Introduction of HARP, a platform designed for systematic research into Human-AI Interaction by providing controlled mock scenarios with live agents.
Frontier Financial Judgement: Can agents tell what might move a stock?
Introduction of the Frontier Financial Judgement benchmark to evaluate AI agents' ability to replicate expert human financial analysis and stock movement predictions.
Scaling Interpretable Transformers with Parity Bottleneck Layers
The ParityTransformer introduces Deep Parity Bottlenecks to create language models that are interpretable by design rather than relying on post-hoc sparse autoencoders.