6 papers · 1 filter
PEARL: Front-Loading Relational Chains for Multi-Hop Table Retrieval
Subeen Ho, Hyeongu Kang, SeongKu Kang +1
While large language models (LLMs) have shown strong capabilities in tabular reasoning, retrieving relevant tables remains challenging due to the fragmented and relational structur…
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…
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…
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…
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…
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…