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Abstract - AlignAtt4LLM: Fast AlignAtt for Decoder-Only LLMs at IWSLT 2026 Simultaneous Speech Translation Task
We describe AlignAtt4LLM, an IWSLT 2026 simultaneous speech translation system for English to German, Italian, and Chinese. The system is a synchronous cascade: Qwen3-ASR with forced alignment produces an incrementally updated source transcript, and Gemma-4 E4B-it translates that prefix under an MT-side AlignAtt policy. To our knowledge, this is the first application of AlignAtt to a decoder-only LLM, where the encoder-decoder cross-attention used by earlier AlignAtt systems is absent. We recover a usable policy by proposing (1) an explicit source span in the prompt, (2) offline selection of translation-specific alignment heads, (3) selective qk-fast replay of the draft-to-source attention block, and (4) runtime query/key capture that preserves model outputs bit-identically. On the IWSLT 2026 development set, AlignAtt4LLM outperforms the supplied baselines for the European target languages, English to German and English to Italian, in both the low-latency regime around 2 seconds and the high-latency regime below 4 seconds CU-LongYAAL. Results for English to Chinese are more mixed, but the method is not tied to Gemma-4: because AlignAtt4LLM only requires a deterministic prompt layout, calibrated attention heads, and query/key capture, the same policy can be reapplied to stronger translation-focused decoder-only MT backbones for non-European target languages.
AlignAtt4LLM:面向仅解码器大语言模型的快速对齐注意力机制——应用于IWSLT 2026同声传译任务 /
AlignAtt4LLM: Fast AlignAtt for Decoder-Only LLMs at IWSLT 2026 Simultaneous Speech Translation Task
1️⃣ 一句话总结
本文提出了一种名为AlignAtt4LLM的实时语音翻译系统,首次将原本用于编码器-解码器模型的注意力对齐策略(AlignAtt)成功迁移至仅解码器的大语言模型(如Gemma-4)上,通过设计显式源语言提示、筛选翻译专用注意力头、快速重放注意力块以及运行时无损捕获查询/键值等创新技术,在英译德和英译意的同声传译任务中,以极低延迟(约2秒)和低延迟(4秒内)均超越了官方基准,为仅解码器模型实现高效流式翻译开辟了新路径。