AAAI

Conversational Learning Diagnosis via Reasoning Multi-Turn Interactive Learning

通过推理的多轮交互学习诊断

Fangzhou Yao, Sheng Chang, Weibo Gao, Qi Liu

AI总结 本文提出ParLD框架，通过多智能体协作实现对话学习中的认知诊断，提升诊断的可靠性和洞察力。

Comments AAAI 2026

I-CAM-UV: Integrating Causal Graphs over Non-Identical Variable Sets Using Causal Additive Models with Unobserved Variables

I-CAM-UV: 在非相同变量集上整合因果图使用带有未观测变量的因果加法模型

Hirofumi Suzuki, Kentaro Kanamori, Takuya Takagi, Thong Pham, Takashi Nicholas Maeda, Shohei Shimizu

AI总结 I-CAM-UV通过整合带有未观测变量的因果加法模型，解决多数据集非相同变量集下的因果图整合问题。

Comments 16 pages, 22 figures, to appear in the 40th AAAI Conference on Artificial Intelligence (AAAI 2026)

LLandMark: A Multi-Agent Framework for Landmark-Aware Multimodal Interactive Video Retrieval

LLandMark：一种用于地标感知多模态交互视频检索的多智能体框架

Minh-Chi Phung, Thien-Bao Le, Cam-Tu Tran-Thi, Thu-Dieu Nguyen-Thi, Vu-Hung Dao

机构 * AI VIETNAM（AI越南） 纠错

AI总结 LLandMark通过多智能体框架实现地标感知的多模态视频检索，结合LLM和OCR技术提升文化场景下的检索能力与可解释性。

Comments Accepted by AAAI 2026 Workshop on New Frontiers in Information Retrieval

Journal ref AAAI 2026 Workshop on New Frontiers in Information Retrieval

MoToRec: Sparse-Regularized Multimodal Tokenization for Cold-Start Recommendation

MoToRec：基于稀疏正则化的多模态分词用于冷启动推荐

Jialin Liu, Zhaorui Zhang, Ray C. C. Cheung

AI总结 MoToRec通过稀疏正则化的多模态分词方法，解决冷启动推荐中的数据稀疏性和新物品表示问题，提升推荐系统性能。

Comments Accepted to AAAI 2026 (Main Track)

MedLA: A Logic-Driven Multi-Agent Framework for Complex Medical Reasoning with Large Language Models

MedLA：基于大语言模型的复杂医学推理多智能体框架

Siqi Ma, Jiajie Huang, Fan Zhang, Yue Shen, Jinlin Wu, Guohui Fan, Zhu Zhang, Zelin Zang

AI总结 MedLA是一种基于大语言模型的逻辑驱动多智能体框架，通过多轮图引导讨论实现透明推理和共识达成，有效提升复杂医学推理性能。

Comments accepted by AAAI-26 (ORAL)