Multilingual 2B speech–language model for ASR and bidirectional speech translation (EN, FR, DE, ES, PT, JA), providing punctuation/truecasing, keyword biasing, and a dual-head CTC encoder to boost transcription accuracy.
7B multilingual translation model optimized for instruction-following and low-latency deployment across 33 languages; provides quantized/FP8/GGUF builds and integrations (vLLM, llama.cpp) for server and on-device inference.
Parallel Chinese→Vietnamese dataset of webnovel (xianxia) text provided in JSON for NMT training and teacher-student distillation. In-domain, ~100K–1M examples with CC-BY-4.0 license — useful for fine-tuning or distillation experiments but limited by narrow genre and small download footprint.
Large streaming-audio dataset for training and evaluating audio-LLMs and audio agents. About 2.28M clips grouped into multi-turn “streams” across six task subsets (ASR, speech translation, audio understanding, voice chat, proactive response, environment-aware); audio shipped as tar shards.
Trains LLMs with reinforcement learning using a surface chrF reward so models learn to extract and apply linguistic signals from rich context for translating completely unseen languages. Demonstrates better zero-shot translation than in-context learning or supervised fine-tuning, framing outcome-based RL as a meta-skill for language learning from context.
A living, crowdsourced dataset of hard-to-translate examples (text, images, audio, video) paired with handcrafted verification rules that flag concrete MT failures. LTBv1 contains 3,456 peer-reviewed examples across many language pairs and accepts ongoing contributions.