Falcon-Edge: A series of powerful, universal, fine-tunable 1.58bit language models.

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance

Falcon 2: An 11B parameter pretrained language model and VLM, trained on over 5000B tokens and 11 languages

Large Language Models: A New Moore's Law?

Falcon-Arabic: A Breakthrough in Arabic Language Models

AMD + 🤗: Large Language Models Out-of-the-Box Acceleration with AMD GPU

Accelerating Vision-Language Models: BridgeTower on Habana Gaudi2

The State Of LLMs 2025: Progress, Problems, and Predictions

A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.

Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER)

arXiv:2606. 07608v1 Announce Type: cross Abstract: We present a systematic study of fine-tuning OpenAI's Whisper large-v3 for Swiss German ASR, using 1,367 hours of broadcast speech paired with Standard German subtitles as weak supervision.

TTS Arena: Benchmarking Text-to-Speech Models in the Wild

MLLP-VRAIN UPV system for the IWSLT 2026 Simultaneous Speech Translation task

arXiv:2606. 17255v1 Announce Type: cross Abstract: This work describes the participation of the MLLP-VRAIN research group in the shared task of the IWSLT 2026 Simultaneous Speech Translation track.

Benchmarking Large Language Models on Floating-Point Error Classification

arXiv:2606. 31308v1 Announce Type: new Abstract: This paper investigates the capability of Large Language Models (LLMs) to detect and classify floating-point errors statically in software code.

Build Low-Latency Multilingual Voice Agents: Open Weights & Full Deployment Control with NVIDIA Magpie TTS