Driff

Terminal Finance hits $280M TVL before launch. Ethena-backed DEX transforms yield-bearing stablecoin trading with sUSDe integration.

Terminal Finance Surpasses $280M TVL: What Makes This Ethena-Incubated DEX Different

Let's learn how MCP differs from traditional APIs and how it safely allows AI models to communicate with the real world. 

MCP vs API: The Key Difference Between Human and Machine Communication

Beyond the Hype: Why 87% of AI Projects Fail and What the 13% Do Differently

Google unveiled Gemini Diffusion, a text diffusion model for code. It promises faster generation and better editing, potentially changing AI-native development.

New Gemini Diffusion Model Promises Text at Five Times the Speed

This article provides the implementation specifics for the Stratified Diffusion models in SAGE Net.

Optimizing SAGE Net: Sequential Training of Stratified Diffusion Models and Full-Body Decoder

This article describes the online inference stage of the model, which predicts 3D avatars in a frame-by-frame manner using a sliding window approach

Temporal Refinement in Stratified Motion Diffusion: Utilizing GRU for Smoothed Full-Body Prediction

This article distinguishes OCA‑proofness from SCP, showing the latter is a stronger collusion‑resistance notion.

Comparing SCP and OCA in Transaction Fee Mechanisms: Core Differences and Results

Evaluation of Dockerized Android: emulator vs real-device testing, reproduced security kill-chains (BlueBorne, CVE-2018-7661), and cross-platform limits.


How Dockerized Android Performs Across Different Operating Systems

If you take the time to notice people around you, you’ll find that they all have unique styles in the way they talk, how they work and what motivates them.

How to Deal With Different People on Your Team 

This article provides the technical implementation details of the Tree-Diffusion architecture using PyTorch and NF-ResNet.

Implementation Details of Tree-Diffusion: Architecture and Training for Inverse Graphics

This article details the Tree Path Algorithm, which finds the first mutation step to convert a source syntax tree into a target tree. 

The Role of Mutation Path Algorithms in Tree-Diffusion Program Synthesis

This article provides a detailed breakdown of the mutation sampling algorithm for Tree-Diffusion, focusing on how to generate syntactically valid replacements.

Controlling Program Length in Tree Diffusion: A Modified Mutation Sampling Algorithm

This conclusion summarizes a novel approach to program synthesis using a neural diffusion model operating on syntax trees. 

The Future of Code Generation: Tree-Diffusion, Limitations, and Research Directions

This article compares a novel denoising diffusion model for code generation (Tree-Diffusion) against two baseline methods, CSGNet and REPL Flow. 

The New Standard for Program Synthesis: How Tree-Diffusion Outperforms CSGNet and REPL Flow

This article describes the experimental evaluation of a new code generation method, Tree-Diffusion, across four domain-specific graphics languages.

Experiments with Tree-Diffusion: Testing a New Code Generation Method on Graphics Languages

This article presents a novel method for program synthesis using denoising diffusion models on syntax trees.

From Images to Programs: A Denoising Diffusion Method for Inverse Graphics

Contrasting traditional methods with the novel approach of using neural diffusion models for iterative code editing. 

The Evolution of Code Generation: A Look at Neural Diffusion, GFlowNets, and Direct Editing

This article introduces Tree-Diffusion, a novel method for code generation that uses neural diffusion models on syntax trees.

Tree-Diffusion: A New Approach to Code Generation with Neural Diffusion Models

A Non-Diffusive Neural Network Method for Solving Hyperbolic Conservation Laws

New NDNN method shows how neural networks can model entropic shock waves in HCLs without artificial diffusion or viscosity.

Can Neural Networks Capture Shock Waves Without Diffusion? This Paper Says Yes

Mab.io challenges Monday, ClickUp, and Asana by ditching endless flexibility for fixed roles and rules, making project management sharper and simpler.

Mab.io vs. Monday, ClickUp, and Asana: A Different Take on Project Management

This article dive deep on the Thinking Machines Lab publication that addresses the challenge of achieving reproducibility in LLM inference

The Unseen Variable: Why Your LLM Gives Different Answers (and How We Can Fix It)

This post will examine four key vocoders: WaveNet, WaveGlow, HiFi‑GAN, and FastDiff. We’ll explain how each model works and what makes them different. Most impo

Inside the Neural Vocoder Zoo: WaveNet to Diffusion in Four Audio Clips

This article presents a cDDPM that conditions on detector data to sample P(x|y), enabling multidimensional unfolding and generalization.

educe Truth Bias and Speed Up Unfolding with Moment‑Conditioned Diffusion

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