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

10 citations · 24 across the 7 of their papers we have counts for

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cs.CL2026

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…

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★ 1 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.CL2024★ 7 cited

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…

cs.CL2024★ 10 cited

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

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…