研究人员开发了 CorPipe 26，该系统赢得了 2026 年多语言共指消解共享任务 (CRAC 2026)。这个改进的系统引入了一个变体，能够在一个模型中同时预测空节点、提及和共指链接。CorPipe 26 表现出色，在 LLM 和无约束赛道上均大幅超越了其他参赛者。 AI
影响 推动了多语言共指消解的进步，有望改善自然语言处理应用中的跨语言理解。
排序理由 详细介绍新系统及其在特定任务上表现的学术论文。
AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →
arXiv:2605.30133v1 Announce Type: new Abstract: We introduce CorPipe 26, our winning submission to the CRAC 2026 Shared Task on Multilingual Coreference Resolution. The fifth edition of this shared task focuses mainly on the comparison of generative LLMs and specialized systems; …
We introduce CorPipe 26, our winning submission to the CRAC 2026 Shared Task on Multilingual Coreference Resolution. The fifth edition of this shared task focuses mainly on the comparison of generative LLMs and specialized systems; additionally, 5 more datasets and 2 new language…
We introduce CorPipe 26, our winning submission to the CRAC 2026 Shared Task on Multilingual Coreference Resolution. The fifth edition of this shared task focuses mainly on the comparison of generative LLMs and specialized systems; additionally, 5 more datasets and 2 new language…