AI Intelligence Archive

Battle-tested pgvector HNSW tuning and hybrid search implementation after hitting severe concurrency bottlenecks in a production RAG pipeline.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...

Distribution regression seeks to learn mappings from probability distributions to response variables and has emerged as a unifying framework for kernel methods, multi-instance learning, and set-valued learning. Despite its success, kernel-…

We study quantization for inner-product estimation when storage and reading have separate budgets. In the static bit-probe model [Yao, 1981], an encoder stores $w$ bits about $x$ before seeing a query $y$, and a reader probes at most $r<w$…

Diversity is a critical property of text corpora, with direct implications for training data curation, test set design, and model generalization. However, its measurement remains fragmented and poorly understood. Existing embedding-based d…

Decision Brain: giving AI the why behind the work, with FalkorDB I built Decision Brain...

You upload a document, ask a question, and get an incomplete answer. You check the source. The...

I Lost a Working n8n Workflow to a Bad Edit — Now Git Versions Every Deploy Part of my...

Reinforcement learning with general utilities optimizes nonlinear functionals of policy-induced occupancy measures. We develop a natural actor-critic method for concave RLGU objectives admitting an exact variational dual representation, wi…

Temporal graph neural networks (TGNNs) have shown strong performance on dynamic graph learning tasks by continuously updating node memories from evolving interactions (i.e., events) and leveraging these memories for downstream predictions.…

Can one sentence manipulate an agent's belief by targeting a single implicit warrant linking evidence to a conclusion? In this paper, we introduce the one-relation attack (ORA), a novel cognitive attack on this inferential relation. ORA lo…

Jailbreak papers report an attack success rate, the share of responses that deliver the harmful request, and read it as a property of the target model. We hold the target model, the prompts and the responses fixed and change only the grade…

PrintBrief: Turning Messy Customer Messages into Print-Ready Orders with Local AI This is...

A general observation in agentic workflows, especially bounded ones, is that the decision space of the LLM, when we separate a decision from generation, starts approaching saturation: the agent meets the same states again and again, and af…

Alzheimer's Disease (AD) detection from speech benefits from both paralinguistic and linguistic cues, yet model training is frequently constrained by limited data. Fine-tuning a large pretrained speech encoder can easily overfit, while a f…

Video generation models synthesize visual sequences from text and image inputs. Extending video generation to long animations requires actions, dialogue, camera coverage, and narrative developments to remain coordinated across scenes. Exec…

Battle-tested comparison of Magnitude's auto-tuning kernel approach against Ollama's static compilation for on-device LLM inference across M2, RTX 4090, and CPU.

A year of building with AI put me on three stages. I liked the message more than the...

Generative AI workflows execute user tasks by composing sequences of LLM calls, where each call performs a sub-task (e.g., summarization or translation), forming a workflow. Executing such workflows requires decisions over workflow structu…

This is a submission for the Hacktoberfest 2026 DEV Challenge: Side Hustle. What I...

Why Flat Vector DBs Break Agent Swarms — And How We Built AgentMesh AI with FalkorDB If you have...

A local-AI receipt scanner: photograph a receipt, let Tesseract + Gemma draft it, correct it, and keep a price history you can actually use. Built around the one honest truth about small models — they draft, you confirm.

Heterogeneous optimization problems require an optimizer to decide not only which candidate solutions to evaluate, but also which objectives and constraints should be evaluated under different costs and fidelities. Existing SOTA methods su…

Retrieval-augmented language models increasingly use multi-step search to solve knowledge-intensive tasks, yet existing systems typically expose retrieval through fixed pipelines or collections of atomic tools. We introduce Retrieval Progr…

A September 2026 paper got coding agents to delete their own session traces on request. If the agent can write the record, it isn't evidence.

Every Game Is Connected — I Built the Graph That Proves It Recommendation engines are...

Large language models (LLMs) are widely used to answer questions from retrieved or user-provided context. However, provided context can be factually true yet out-of-scope, describing a different entity, time, or location from the one the q…

Analytic continual learning (ACL) methods such as ACIL and GACL fit a ridge-regression classifier head on frozen features via the Sherman-Morrison-Woodbury identity, achieving exemplar-free, exact updates. A separate line of work, Progress…

We provide new statistical insights into designing stochastic optimization methods. By modeling the gradient via a normal distribution, we argue that the stochastic gradient should be whitened using its covariance. We give an online method…

Existing evaluations of LLM-based code optimization primarily measure end-to-end speedup, obscuring whether a model actually performs the intended optimization. For compiled languages, this is especially problematic: observed gains may ref…

Biomechanical movement recordings are continuous, high-dimensional time series, and analyzing them without manually labeling them requires representations that capture how movements evolve over time. Most unsupervised representation-learni…

Most long-horizon forecasters emit the complete future in one pass. We ask whether a compact operator can instead be reused to emit contiguous future blocks, trading stored parameters for sequential computation. Recursive Functional Decomp…

Local coding agents can extend their reach by consulting a stronger cloud model. Such consultations, however, often expose the repository's private identifiers, file paths, and source code. Host-side masking hides recognized identifiers bu…

A marketing contractor called alice.moreno clicks the wrong link. Someone on the security team now...

What I Built PrivateDesk is a local document Q&amp;A app for small professional offices:...

This is a submission for the Hacktoberfest 2026 Week 2 challenge. What I Built When a...

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle ...

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle. ...

What I Built CertProof makes certificates for events, then checks its own work. You pick...

The headless command, JSON flag, permission setup, resume and exit code for Claude Code, Codex, Gemini CLI, Copilot CLI and OpenCode, from current docs.