5 papers
ARHN: Answer-Centric Relabeling of Hard Negatives with Open-Source LLMs for Dense Retrieval
Hyewon Choi, Jooyoung Choi, Hansol Jang +4
Neural retrievers are often trained on large-scale triplet data comprising a query, a positive passage, and a set of hard negatives. In practice, hard-negative mining can introduce…
LGAI-EMBEDDING-Preview Technical Report
Jooyoung Choi, Hyun Kim, Hansol Jang +6
This report presents a unified instruction-based framework for learning generalized text embeddings optimized for both information retrieval (IR) and non-IR tasks. Built upon a dec…
INSTRUCTIR: A Benchmark for Instruction Following of Information Retrieval Models
Hanseok Oh, Hyunji Lee, Seonghyeon Ye +4
Despite the critical need to align search targets with users' intention, retrievers often only prioritize query information without delving into the users' intended search context.…
ANNA: Enhanced Language Representation for Question Answering
Changwook Jun, Hansol Jang, Myoseop Sim +4
Pre-trained language models have brought significant improvements in performance in a variety of natural language processing tasks. Most existing models performing state-of-the-art…
Korean-Specific Dataset for Table Question Answering
Changwook Jun, Jooyoung Choi, Myoseop Sim +3
Existing question answering systems mainly focus on dealing with text data. However, much of the data produced daily is stored in the form of tables that can be found in documents…