AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,629 papers
We present a computational framework for multi‑dimensional value assessment, designed to address a structural problem shared by historical evaluation and AI value alignment: how to adjudicate among incommensurable values without collapsing them into a single score. Mainstream approaches to value aggregation seek a corr...
We introduce Grouped-Query Latent Sparse Attention (GQLSA), a novel attention mechanism that integrates latent compression, grouped-query sharing, and block-sparse attention into a unified hardware-native architecture. GQLSA achieves linear O(T) complexity in sequence length, a 3.8x speedup over multi-head attention at...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22662611. Review of "Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling" Summary This preprint asks whether LLMs can be post-trained for expensive,...
Retrieval-Augmented Generation (RAG) combines information retrieval with language generation to improve the grounding of generated answers in a source document, addressing a central weakness of purely parametric large language models: the tendency to produce fluent but unsupported statements. This study designs, implem...
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A method for digital analysis of threatening letters written in the Croatian language using machine learning algorithms, built upon the autoencoder architecture in combination with two text style vectorization methods.
Retrieval-augmented generation (RAG) grounds a language model in retrieved documents, which reduces hallucination but creates a new attack surface: if retrieved text is tampered with, the model may repeat the falsehood. We study how much a small quantized model, Llama 3.1 8B, degrades when a fraction of its retrieved c...
v1.8.0 (2026-09-08). Version DOI: recorded once minted (concept 10.5281/zenodo.22537318). Commits `d786116`/`8954bcf` (Religious Attribution Non-Collapse), `8be7433`/`ef3adc7`/`270c2af` (executable-equations registrar review), `cb03ab6` (Internal-Consistency ladder + mechanical clearing fixes), `fd57ffd` (consistency-g...
FAVE (Foveated Adaptive Visual Encoding), a lightweight variable-resolution ViT that encodes externally selected regions at high acuity while preserving native geometry, is introduced and integrated as a complementary local branch in FastVLM.
Q2D-Web is introduced, a large-scale agentic retrieval benchmark consisting of a 190M-document web corpus and 70k agentic search queries in ten languages, reformulated from real-world user queries in production systems, and benchmark 13 retrievers including lexical, dense, and late-interaction models.
This work presents an RS-specific formulation of the region selection paradigm, previously explored in natural-image MLLMs, and extends it to temporal change localization over multi-image sequences, and constructs a multi-task training and evaluation suite spanning localization, referring expression, visual grounding,...
This work provides a preliminary framework for low-resource Sinhala diachronic analysis, highlighting the trade-offs between model sensitivity and data availability.
Social interaction is central to children's language learning, but the effects of different forms of caregiver feedback are difficult to isolate in naturalistic data. We use child-like language models as controlled learners to test which forms of feedback support grammatical development. Small GPT-2-style models are pr...
A Blog post by NVIDIA on Hugging Face
Data Mining & Modeling
A Blog post by Ai2 on Hugging Face
A Blog post by IBM Research on Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
A Blog post by IBM Granite on Hugging Face
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