第28届欧洲人工智能会议（ECAI 2025）于2025年10月25日至30日在意大利博洛尼亚举行，由欧洲人工智能协会（EurAI）与意大利人工智能协会（AIxIA）联合主办。作为人工智能领域的重要国际学术盛会，ECAI 2025 面向全球学者、产业界与青年研究者，集中展示人工智能的最新理论、算法与应用进展，并促进跨学科、跨地域的交流合作。本届大会秉持“人工智能将成为全面理解可持续发展主题的关键，帮助人类洞察地球、生态系统与社会复杂性”的理念，推动跨学科研究与合作，探索AI服务全球可持续发展的创新路径。在此背景下，我们的研究工作聚焦于大语言模型的指令归纳，面向多样化任务自动化地归纳出高质量的自然语言指令，以充分激发大语言模型在下游任务中的能力。

Marta Kwiatkowska进行主题报告

实验室研究生韩雨辰、董照坤同学的论文《Adaptive Instruction Induction for Enhancing Large Language Model Performance》被ECAI 2025会议录用。韩雨辰同学在大会作口头报告，与来自全球的专家学者分享了研究成果与最新进展。

《Adaptive Instruction Induction for Enhancing Large Language Model Performance》

Instructions, as the primary means of using large language models (LLMs), significantly impact the results. Automatically inducing instructions from few-shot instances is meaningful, yet the induced instructions suffer from two inherent divergences: (1) systematic discrepancies across tasks, and (2) instance-level heterogeneity within a task. To address these challenges, inspired by human analogical reasoning, we propose AdaIn, an iteratively adaptive instruction induction framework that leverages instance-level structural similarities. AdaIn groups instances by data features to induce tailored instructions, and adaptively applies them to new samples. Instruction performance is further utilized to guide updates,, enabling iterative identification and refinement of ineffective instructions. We conducted experiments on different tasks to verify our method and the results demonstrate that it outperforms the SOTA results. Ablation experiments indicate that the adaptive strategy in induction and selection instruction contributes much to performance.

韩雨辰同学参加ECAI 2025会议

韩雨辰同学进行相关论文口头汇报