10 citations · 24 across the 7 of their papers we have counts for
8 papers
IndicFDB: Benchmarking Full-Duplex Voice Agents across Indian Languages
Rajarshi Roy, Shobhit Banga, Jonathan Raiman +12
Full-duplex voice agents must handle pauses, take turns, backchannel, and respond to user interruptions in real time. Full-Duplex-Bench evaluates these behaviors, but its English-o…
VoiceChat-TTS: A Low-Latency Continuous Speech Synthesis Model for Interactive Agents
Edresson Casanova, Jaehyeon Kim, Mariana Graterol Fuenmayor +17
Spoken dialogue is a natural form of human--computer interaction, yet most speech language models remain limited to turn-based operation and lack real-time adaptability, such as us…
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…
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…
CircuitVAE: Efficient and Scalable Latent Circuit Optimization
Jialin Song, Aidan Swope, Robert Kirby +4
Automatically designing fast and space-efficient digital circuits is challenging because circuits are discrete, must exactly implement the desired logic, and are costly to simulate…
Nemotron-4 340B Technical Report
Nvidia, :, Bo Adler +80
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open…
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…
ChatQA: Surpassing GPT-4 on Conversational QA and RAG
Zihan Liu, Wei Ping, Rajarshi Roy +4
In this work, we introduce ChatQA, a suite of models that outperform GPT-4 on retrieval-augmented generation (RAG) and conversational question answering (QA). To enhance generation…