Text-Generation Pipeline on Intel® Gaudi® 2 AI Accelerator

Faster assisted generation support for Intel Gaudi

Faster Text Generation with TensorFlow and XLA

Accelerating Protein Language Model ProtST on Intel Gaudi 2

Building an AI Text Detector From Scratch

An End-to-End Project With Dataset Construction, Model Training, Local Deployment, and RLVR

Assisted Generation: a new direction toward low-latency text generation

Performance Optimization and Comparative Analysis of Generative AI Models on Advanced Accelerators

arXiv:2607. 05400v1 Announce Type: cross Abstract: Generative AI models, such as Large Language Models (LLMs) and diffusion models, have demonstrated impressive performance across a wide range of tasks.

Little Brains, Big Feats: Exploring Compact Language Models

arXiv:2606. 30062v1 Announce Type: cross Abstract: While large language models have been dominating the research landscape recently, small language models remain highly relevant across various domains; yet, they receive far less attention.

Little Brains, Big Feats: Exploring Compact Language Models

While large language models have been dominating the research landscape recently, small language models remain highly relevant across various domains; yet, they receive far less attention. In this study, we investigate how smaller language models perform during the generation stage within a Retrieval-Augmented Generation (RAG) system.

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators

arXiv:2607. 11211v1 Announce Type: new Abstract: The popularity of large language models (LLMs) escalates an ongoing demand for effective inference.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent

arXiv:2507. 02259v2 Announce Type: replace-cross Abstract: Despite improvements by length extrapolation, efficient attention and memory modules, handling infinitely long documents with linear complexity without performance degradation during extrapolation remains the ultimate challenge in long-text processing.

Agentic Artificial Intelligence for Multistage Physics Experiments at a Large-Scale User Facility Particle Accelerator

arXiv:2509. 17255v2 Announce Type: replace-cross Abstract: We present the first language-model-driven agentic artificial intelligence (AI) system to autonomously execute multi-stage physics experiments on a production synchrotron light source.

Accelerating Document AI