August newsletter is out
The August edition of my sponsors-only monthly newsletter is out. If you are a sponsor (or if you start a sponsorship now) you can access it here. This month: We got more details on OpenAl's accidental cyberattacks…
Topic - Edition
AI
How to Start an LLM-Assisted Java Project
Most context engineering goes into supplying the model with knowledge. For a Java project nearly all of that is redundant, because the model already read the specs. What it does not have is an opinion about how your…
I got tired of AI resume spam and ghost jobs, so I built an open-source CLI agent for developers
Job hunting in 2026 is mathematically broken. Recruiters use ATS bots to reject candidates in 6 seconds. Companies post ghost jobs that stay open for months. And the market is flooded with paid SaaS tools charging…
Your AI Agent's Reasoning Just Stopped Traveling Between Models
For the last two years, most of us building with large language models made a quiet assumption without ever writing it down anywhere. We assumed that the thinking a model produces is just text. Tokens in, tokens out. If…
Practical LLM Agent Development: Architecture, Tools and Best Practices
Large Language Models have moved beyond simple text generation. Modern applications can use LLMs as the reasoning layer of an AI agent that retrieves information, calls tools, interacts with APIs, and completes…
GPT-6 Astra: Everything You Need to Know About OpenAI’s New Model
GPT-6 Astra can operate computers, build software, solve research problems, and hunt zero-day vulnerabilities. The bigger change is that OpenAI increasingly expects you to give AI work instead of prompts.
A Low-Cost, Open Platform for End-to-End Autonomous Driving on a Miniature Ackermann Vehicle
arXiv:2609.04147v1 Announce Type: new Abstract: This paper presents a low-cost, open experimental platform for research in end-to-end autonomous driving with miniature Ackermann vehicles. The platform combines a…
Identification of Bivariate Causal Directionality Based on Anticipated Asymmetric Geometries
arXiv:2603.26024v3 Announce Type: replace Abstract: Identification of causal directionality in bivariate numerical data is a fundamental research problem with important practical implications. This paper presents two…
Activation-Keyed Momentum: An Anisotropic Momentum Update via the Delta Rule
arXiv:2608.19491v2 Announce Type: replace Abstract: Most modern optimizers form their momentum as an exponential moving average (EMA) of past gradients, forgetting every direction at one fixed rate. However, the inputs…
BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training
arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due to massive memory…
EPIC: Explicit Posterior Item Conditioning for Semantic ID Diffusion Recommendation
arXiv:2609.03522v1 Announce Type: cross Abstract: Semantic ID (SID) generative recommendation predicts the next item by generating a short tuple of discrete tokens. Recent masked-diffusion methods improve this process…
FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience
arXiv:2609.03241v1 Announce Type: new Abstract: A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal verifiers provide reliable yet sparse supervision, while dense…
Evaluating Graph Neural Networks for Change-Criticality Classification in Maritime Navigation Charts
arXiv:2609.02996v1 Announce Type: new Abstract: Graph neural networks (GNNs) are a class of neural networks suitable for learning on graph-structured data. Their application to spatial data is a natural extension,…
ScoreMix: Synthetic Data Generation by Score Composition in Diffusion Models Improves Recognition
arXiv:2506.10226v3 Announce Type: replace-cross Abstract: Synthetic data generation is increasingly used in machine learning for training and data augmentation. Yet, current strategies often rely on external foundation…
Subspace Inference Enables Efficient Active Reward Learning from Preferences
arXiv:2609.04066v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) has emerged as a powerful yet sample-inefficient approach for learning reward models from human preferences, making…
Sensing Which Modality Matters: Evidence-Gated Regularization for Robust VLA Policies
arXiv:2609.03142v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies fuse multimodal sensory inputs, but training on limited and homogeneous robot demonstrations encourages spurious inter-sensor…
Parameterised graph theory for tensor networks: entanglement rerouting, structural simplification, and agnostic tomography
arXiv:2609.04165v1 Announce Type: cross Abstract: Parameterised graph theory studies how the complexity of graph-theoretic problems depends on structural parameters of the input graph. This perspective has proved useful…
RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting
arXiv:2609.03937v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) complements parametric models with retrieved external evidence. The same idea is attractive for continuous-output regression, but…
Robust PAC Learning of Concurrent Stochastic Games
arXiv:2609.04189v1 Announce Type: new Abstract: We introduce the first Probably Approximately Correct (PAC) learning framework for general-sum concurrent stochastic games (CSGs) with transition uncertainty, while…
RobustSeiz: An Open-Source Framework for Benchmarking the Robustness of EEG Seizure Detection Models
arXiv:2609.04007v1 Announce Type: new Abstract: Despite strong performance on held-out electroencephalography (EEG) data, seizure detectors may fail under real-world acquisition variability, artifacts, and adversarial…
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