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3,317 papers
Multilingual LLM benchmarks omit Slovak, a morphologically rich West Slavic language of five million speakers, or cover it only by machine translation. We present sk-bench, a native-first Slovak benchmark with 30 datasets (33 scored task variants) across ten skill categories. Eleven resources are introduced or first pa...
Large language model agents can improve across tasks by retaining reusable skills distilled from prior interactions. Recent work jointly optimizes task execution and skill extraction, enabling the policy and skillbank to co-evolve. However, as the actor continues learning, rewarding skill proposals through their reuse...
Flow Language Models (FLMs) have emerged as a continuous-state alternative to discrete diffusion language models, yet the role of their continuous representations in reasoning remains unclear. We investigate this question by comparing the reasoning efficiency of FLMs and discrete diffusion models, measured by solution...
Language models are more and more often asked for structured output: JSON that follows a schema, or a tool call with typed arguments. A small machine, an automaton, enforces the format by forbidding the tokens that would break it. We observe that this machine has a rare property: from any of its states, each token lead...
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An agentic system issues several structurally different kinds of LLM calls. It routes intent, classifies actions, grounds language in a device registry, plans multi-agent pipelines and writes the Python code those pipelines run. The difficulty of these call sites varies by an order of magnitude, yet in practice a singl...
As small language models (SLMs) are increasingly deployed on resource-constrained and on-device platforms, including as components of agentic systems, the integrity of locally stored model parameters becomes an important safety concern. We investigate whether safety-sensitive behavior in LLaMA-2-7B-Chat is concentrated...
This preprint develops an end-to-end causal account of how information acquires behavioral control in language models. Across a coordinated series of mechanistic studies, we trace the computation from distributed relational and typed representations, through task- and recipient-dependent qualification, contextual multi...
Large language models now write a substantial share of new source code, yet the mechanisms by which organisations establish confidence in that code have hardly changed. Independent testing indicates that AI-generated code introduces security weaknesses in close to half of evaluated tasks, while European regulation – no...
This study developed a lightweight LINE-based mobile knowledge chatbot for the Level B Computer Hardware Repair certification subject and examined its instructional effectiveness in comparison with ChatGPT. The system was deployed through the LINE mobile messaging platform, allowing learners to access certification-rel...
PRISM-LoRA is proposed, a replay-free framework that repeatedly trains a single LoRA module, merges its update into the backbone, and reinitializes it for the next task, unlike LoRA-based continual-learning approaches that retain task-specific modules or allocate separate task-specific learning spaces.
A living paper, student tutorial, library of 16 tested parametric OpenSCAD designs for biology labs (benchware, tools, quick fixes and parts of full instruments), and Prompt-to-Bench-16, a benchmark that scores language-model-written OpenSCAD against hidden geometric checks. Includes an evaluation of small open-weight...
NeST: Neuron-Selective Tuning for Efficient Safety Alignment A lightweight and structure-aware safety alignment framework that selectively adapts safety-relevant neurons to strengthen refusal behavior while preserving the model's general capabilities. 🚀 Overview Safety alignment is essential for reliable deployment of...
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
A Blog post by IBM Research on Hugging Face
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