All Articles
17188 articles total
Fully Trainable Deep Differentiable Logic Gate Networks and Lookup Table Networks
A new method for optimizing connections in deep differentiable logic gate networks (LGNs) and lookup table networks (LUTNs) is proposed, drastically reducing gate requirements.
Zig Creator Calls Spade a Spade, Anthropic Blows Smoke
A discussion involving the creator of Zig regarding his views on Anthropic's marketing and technical claims.
Interrail: 6,379Km and 13 Countries over 7 weeks
A travelogue describing a 7-week journey across 13 countries via Interrail.
Frieve Vinyl Explained – Microscopic stylus/groove physics simulation
A technical simulation exploring the microscopic physics of how a stylus interacts with vinyl grooves.
The Graph That Should Be Front-Page News
An article presenting a significant graph and its implications, though the content snippet is minimal.
Berkshire's $397B Bet Against an Overheated Market
Analysis of Berkshire Hathaway's massive financial bet against the current market conditions.
Waze is getting a bunch of new AI-powered features
Waze is integrating Google's Gemini AI to enable conversational voice commands for traffic reporting and destination searches.
Geopolitical alignment: Endorsement effects in large language models
Research demonstrating that LLMs exhibit geopolitical biases, rating policies lower when endorsed by non-Western entities like China or Russia.
Risk-Aware General-Utility Markov Decision Processes
A paper proposing a risk-aware framework for General-Utility Markov Decision Processes using Monte Carlo Tree Search to optimize risk-averse behaviors.
Creativity, honesty and designed forgetting emerge in small hyperbolic language models
Exploration of how small hyperbolic language models can achieve creativity, honesty, and designed forgetting for trustworthy companion AI.
Automatic Thematic Indexing of Large Literary Corpora: A Machine Learning Approach to Voltaire's Complete Works
Research on using machine learning, specifically 4-bit quantized Mistral models with LoRA, for the automatic thematic indexing of Voltaire's literary works.
ReGen: Hierarchical Multi-Prompt Representation Generation for Efficient Waveform Diffusion Models
ReGen is a hierarchical multi-prompt representation generation framework that improves waveform generation quality in diffusion models, specifically for text-to-speech.
A Personalized Computational Framework for Assessing the Sufficiency of Partially Observed Data in Healthcare AI models
The authors introduce Feature Sufficiency Analysis (FSA) to determine if a subset of available clinical features is enough for an AI model to reach full-feature-capacity in healthcare.
Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations
A large-scale study on vLLM configurations reveals that attention kernel type and prefix caching significantly impact energy, performance, and occasionally accuracy.
Generative Communications: Overview, Technologies, and Trends
This paper proposes Generative Communications (GenCom), a 6G network paradigm where large AI models drive semantic understanding and content generation rather than simple bit transmission.
Interference and Retention in Continual Learning
The paper introduces Interference-Gated Functional Allocation (IGFA), a replay-free method to eliminate forgetting in continual learning by modeling forgetting as task interference.
Tactile and Vision Conditioned Contact-Centric Control for Whole-Arm Manipulation
TACTIC is a receding-horizon controller for whole-arm robot manipulation that combines RGB-D, tactile sensing, and proximity representations for better contact-centric control.
Git-Assistant: Planning-Based Support for Updating Git Repositories
Git-Assistant combines LLMs with automated planning to help developers execute complex git operations more reliably than using LLMs alone.
All you need is SAMPAT
SAMPAT is a three-layer neural architecture that provides fully interpretable, closed-form algebraic expressions while remaining competitive with deep neural networks.
LLMs for health: Perceived benefits, risks, intention to use AI chatbots, and willingness to self-disclose across sensitive health topics
A study on Dutch participants' perceptions of AI chatbots for health reveals that usage intention is driven by perceived benefits and risks rather than the topic sensitivity.