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cs.IR2026

Improving Scientific Document Retrieval with Academic Concept Index

Jeyun Lee, Junhyoung Lee, Wonbin Kweon +7

Adapting general-domain retrievers to scientific domains is challenging due to the scarcity of large-scale domain-specific relevance annotations and the substantial mismatch in voc…

cs.IR2026

MUDY: Multi-Granular Dynamic Candidate Contextualization for Unsupervised Keyphrase Extraction

Hyeongu Kang, Susik Yoon

Keyphrase extraction aims to automatically identify concise phrases that effectively represent the content of a document. While recent methods leveraging pre-trained language model…

cs.IR2026

SPRINT: Scalable and Predictive Intent Refinement for LLM-Enhanced Session-based Recommendation

Gyuseok Lee, Wonbin Kweon, Zhenrui Yue +5

Large language models (LLMs) have enhanced conventional recommendation models via user profiling, which generates representative textual profiles from users' historical interaction…

cs.IR2026

Why These Documents? Explainable Generative Retrieval with Hierarchical Category Paths

Sangam Lee, Ryang Heo, SeongKu Kang +3

Generative retrieval directly decode a document identifier (i.e., docid) in response to a query, making it impossible to provide users with explanations as an answer for ``why is t…

cs.IR2026

CREAM: Continual Retrieval on Dynamic Streaming Corpora with Adaptive Soft Memory

HuiJeong Son, Hyeongu Kang, Sunho Kim +4

Information retrieval (IR) in dynamic data streams is a crucial task, as shifts in data distribution degrade the performance of AI-powered IR systems. To mitigate this issue, memor…