Faster Text Generation with TensorFlow and XLA

DiffusionGemma: 4x faster text generation

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

Benchmarking Text Generation Inference

Nexus: Structured Synergy for Efficient Text-to-Image Generation using Rectified Flow Model

Diffusion and flow matching models have made significant progress in text-to-image generation, yet high computation, quadratic complexity, and large memory footprint hinder high-resolution synthesis and edge deployment. We propose Nexus, which integrates sparse architecture, linear complexity, and low-bit quantization.

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

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.

Introducing multi-backends (TRT-LLM, vLLM) support for Text Generation Inference

Faster IndexTTS-2: Accelerating and Streaming Autoregressive Zero-Shot Text-to-Speech Synthesis on GPUs

arXiv:2607. 21042v1 Announce Type: new Abstract: Autoregressive text-to-speech models achieve strong naturalness but suffer from slow inference due to sequential token generation, limiting their deployment in production applications that require low latency.

Welcome aMUSEd: Efficient Text-to-Image Generation

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.

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.

Accelerating Document AI