activity
20242026
most citedALR: A Retrieve-then-Reason Framework for Long-context Question Answering

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Voxtral TTS

Mistral-AI, :, Alexander H. Liu +186

We introduce Voxtral TTS, an expressive multilingual text-to-speech model that generates natural speech from as little as 3 seconds of reference audio. Voxtral TTS adopts a hybrid…

cs.LG2026

A CDF-First Framework for Free-Form Density Estimation

Chenglong Song, Mazharul Islam, Lin Wang +2

Conditional density estimation (CDE) is a fundamental task in machine learning that aims to model the full conditional law , beyond mere poi…

cs.CL2025

Command A: An Enterprise-Ready Large Language Model

Team Cohere, :, Aakanksha +227

In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…

cs.CL2025

Rope to Nope and Back Again: A New Hybrid Attention Strategy

Bowen Yang, Bharat Venkitesh, Dwarak Talupuru +4

Long-context large language models (LLMs) have achieved remarkable advancements, driven by techniques like Rotary Position Embedding (RoPE) (Su et al., 2023) and its extensions (Ch…

cs.CL2024

Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier

John Dang, Shivalika Singh, Daniel D'souza +42

We introduce the Aya Expanse model family, a new generation of 8B and 32B parameter multilingual language models, aiming to address the critical challenge of developing highly perf…

cs.CL20241 cited

ALR: A Retrieve-then-Reason Framework for Long-context Question Answering

Huayang Li, Pat Verga, Priyanka Sen +5

The context window of large language models (LLMs) has been extended significantly in recent years. However, while the context length that the LLM can process has grown, the capabi…