6 papers
Learning User-Aware Recall: Personalized Retrieval in Long-Term Conversational Memory
ZhiShu Jiang, Haibo Liu, Xin Shen +6
Long-term conversational agents are expected to remember past interactions, but memory is useful only when the right evidence is recalled for the right user. Existing memory-augmen…
SciEGQA: A Dataset for Scientific Evidence-Grounded Question Answering and Reasoning
Wenhan Yu, Zhaoxi Zhang, Wang Chen +5
Scientific documents contain complex multimodal structures, which makes evidence localization and scientific reasoning in Document Visual Question Answering particularly challengin…
CMRAG: Co-modality-based visual document retrieval and question answering
Wang Chen, Wenhan Yu, Guanqiang Qi +5
Retrieval-Augmented Generation (RAG) has become a core paradigm in document question answering tasks. However, existing methods have limitations when dealing with multimodal docume…
DuCCAE: A Hybrid Engine for Immersive Conversation via Collaboration, Augmentation, and Evolution
Xin Shen, Zhishu Jiang, Jiaye Yang +13
Immersive conversational systems in production face a persistent trade-off between responsiveness and long-horizon task capability. Real-time interaction is achievable for lightwei…
Decide Then Retrieve: A Training-Free Framework with Uncertainty-Guided Triggering and Dual-Path Retrieval
Wang Chen, Guanqiang Qi, Weikang Li +3
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating external knowledge, but existing approaches indiscriminately trigger retrieval and rely…
PAIRS: Parametric-Verified Adaptive Information Retrieval and Selection for Efficient RAG
Wang Chen, Guanqiang Qi, Weikang Li +3
Retrieval-Augmented Generation (RAG) has become a cornerstone technique for enhancing large language models (LLMs) with external knowledge. However, current RAG systems face two cr…