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cs.CL2026

Unified Audio Intelligence Without Regressing on Text Intelligence

Zhifeng Kong, Sang-gil Lee, Jaehyeon Kim +17

Audio intelligence involves understanding, reasoning about, and generating both audio and speech. In this work, we introduce Nemotron-Labs-Audex-30B-A3B (Audex), a unified audio-te…

cs.CL2026

Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aaron Blakeman +571

We introduce Nemotron 3 Ultra, a 550 billion total and 55 billion active parameter Mixture-of-Experts Hybrid Mamba-Attention language model. We pre-trained Nemotron 3 Ultra on 20 t…

cs.CL20261 cited

PersonaPlex: Voice and Role Control for Full Duplex Conversational Speech Models

Rajarshi Roy, Jonathan Raiman, Sang-gil Lee +5

Recent advances in duplex speech models have enabled natural, low-latency speech-to-speech interactions. However, existing models are restricted to a fixed role and voice, limiting…

cs.CL2025

NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Chankyu Lee, Rajarshi Roy, Mengyao Xu +4

Decoder-only LLM-based embedding models are beginning to outperform BERT or T5-based embedding models in general-purpose text embedding tasks, including dense vector-based retrieva…

cs.CL2024

ChipNeMo: Domain-Adapted LLMs for Chip Design

Mingjie Liu, Teodor-Dumitru Ene, Robert Kirby +39

ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design. Instead of directly deploying off-the-shelf commercial or open-source LLMs, we…