AI Intelligence Archive

We need studies on conversational AI (CAI) at scale to understand human behavior and shape CAI design. However, fragmented reporting of systems and study configurations hinders replication, extension, and knowledge accumulation. We present…

We introduce QuranicMMLU, a benchmark for evaluating generative AI on Quranic Arabic across multiple dimensions of linguistic complexity. Existing Quranic benchmarks center on general question answering and semantic retrieval, without prob…

Every multiparameter persistence vectorization we know of carries a one-sided Lipschitz upper bound and nothing below it: without a lower gauge there is no sense in which the features are faithful, and no per-prediction guarantee can be bu…

Vision-language models (VLMs) rely on storing and transferring appropriate information across their sub-components. Verifying that the VLMs exhibit desired behaviours, while avoiding harmful ones, is central to their reliable deployment. Y…

Gating the value pathway of attention reportedly improves language model pretraining, and prior studies disagree on why. We argue and provide experimental evidence that such gates supply two different things that softmax attention lacks: a…

1. ¿Qué es Amazon Bedrock AgentCore? Es la plataforma de AWS para construir, desplegar y...

Computer-use agents (CUAs) have advanced along two separate lines: graphical interaction and software development through code and the command line. Real digital work requires both, interleaved rather than stacked end to end. We study hybr…

LLM agents in social simulation revise their opinions implicitly, in context: how open an agent is to persuasion can neither be specified nor verified, and collective outcomes inherit the model's training prior. We introduce Bayesian Chron…

Large language models can hold knowledge they do not report. A model may sandbag on a capability evaluation, or answer against what it internally knows, and its outputs alone cannot tell whether it is hiding an answer or simply does not ha…

The prediction of critical heat flux (CHF), a key safety-related quantity in nuclear thermal hydraulics, remains an important challenge due to its direct relationship with fuel performance and reactor safety. Recent studies have demonstrat…

Nvidia projected a doubling of semiconductor shipment volume next year alongside a 70 percent revenue increase. In an industry facing four-year transformer backlogs and extended utility interconnection queues, shipping twice as much silico…

So as some of you know, I had a technical interview with Wasmer today. I was up till midnight last...

I was building a small app where an LLM returns a recipe as JSON and the UI fills in as the answer...

An LLM doesn't "know" that Paris is the capital of France the way a database row knows it. It doesn't...

kagent v1.0.0-alpha1 swaps its agent API for AgentInstance: checkpoint and fork a conversation, resume from a golden snapshot, run Claude Code as...

Two CEL authorization gotchas in agentgateway: matchExpressions entries are OR'ed, and llm.requestModel is empty at the traffic phase. One fails open.

What if your AI assistant could check your store's WhatsApp inbox, look up an order, and send the...

A streaming AI test becomes brittle the moment it expects this exact sequence: Hel → Hello →...

Subtitle: A practical look at failure modes, query routing, hybrid retrieval, and knowing when...

git blame Told Me I Wrote 767 Lines I Didn't Write Before writing about a gate, I checked...

Claude didn’t get smarter. We changed everything around it. Somehow, 6.5 points appeared between...

Build a read-only AI agent in Kiro Crew that audits AWS for security and cost, cites real resource IDs, computes real pricing, and cannot change a thing.

AI coding tools can dramatically speed up development, but only when you give them enough context and...

Empirical evaluation is central to recommender-systems (RecSys) research, but turning experimental designs into executable code remains a manual and error-prone task. We present AutoRecLab, a Python-based autonomous RecSys lab that automat…

Nearly 90% of drugs entering clinical development ultimately fail, despite billions of dollars in investment. Pharmaceutical companies therefore rely on clinical development planning (CDP) and probability of technical and regulatory succes…

Large language models (LLMs) have achieved state-of-the-art performance across a wide range of tasks, motivating two important aspects of deployment: inference efficiency and output provenance, which can be tackled by speculative sampling …

LLMs are increasingly used in social simulations for socially interactive agents and robots, offering more flexibility than rule-based systems. However, even though they mimic human behaviour very well, there is a persistent alienness to t…

A North Star Metric is one number that represents value delivered. That is the whole...

On-device inference is booming, but the momentum is almost all in language models. Diffusion pipelines are memory hungry, latency-sensitive, and require orchestrating an embedder, a transformer, a decoder, and often further postprocessing …

I've been using AI coding agents heavily, and I kept running into the same problem: Useful...

Long transcripts are costly inputs for downstream NLP systems and often contain irrelevant context. We study query-conditioned topic localization: predicting the sentence span in a transcript that best addresses a topic-title query. To imp…

Frontier language models now produce professional deliverables that expert graders judge to match human work on a substantial share of economically valuable tasks, yet most enterprise GenAI initiatives fail to show a measurable business ef…

Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized data scenario, this task is commonly solved using deep clustering methods that utilize de…

Blind and low-vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing vision-language-model-based assistants can provide semantic descriptions but may introduce latency,…

Speculative decoding accelerates LLM inference by drafting multiple tokens in parallel, with tree-based methods further improving efficiency through hierarchical structures. Dynamic-tree methods such as EAGLE-3 perform well under greedy de…

This paper presents a novel framework integrating Bayesian physiological modeling with optimal control strategies to achieve uncertainty-aware, personalized hemodynamic regulation during fluid resuscitation. An uncertainty-aware variationa…

Adaptive optimization methods such as AdaGrad and Adam are widely used in modern neural-network training, but their adaptive scaling is primarily designed for vector-valued parameters and does not explicitly exploit matrix structure. Recen…

Multimodal survival models can combine complementary prognostic information from whole-slide images and genomic profiles, but effective fusion remains challenging amid external cohort shift and computational complexity. To address these ch…

Background: Just-in-time adaptive interventions (JITAIs) can use behavioral data to adapt support to changing contexts, but many rely on predefined rules and manual configuration. Objective: We developed a proof-of-concept sleep JITAI usin…