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20232026
most citedResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models

13 citations · 29 across the 22 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.IR2024

Efficient Long Context Language Model Retrieval with Compression

Minju Seo, Jinheon Baek, Seongyun Lee +1

Long Context Language Models (LCLMs) have emerged as a new paradigm to perform Information Retrieval (IR), which enables the direct ingestion and retrieval of information by proces…

cs.SE2024

Rethinking Code Refinement: Learning to Judge Code Efficiency

Minju Seo, Jinheon Baek, Sung Ju Hwang

Large Language Models (LLMs) have demonstrated impressive capabilities in understanding and generating codes. Due to these capabilities, many recent methods are proposed to automat…

cs.CL2024

Unified Multimodal Interleaved Document Representation for Retrieval

Jaewoo Lee, Joonho Ko, Jinheon Baek +2

Information Retrieval (IR) methods aim to identify documents relevant to a query, which have been widely applied in various natural language tasks. However, existing approaches typ…

cs.CL2024

Database-Augmented Query Representation for Information Retrieval

Soyeong Jeong, Jinheon Baek, Sukmin Cho +2

Information retrieval models that aim to search for documents relevant to a query have shown multiple successes, which have been applied to diverse tasks. Yet, the query from the u…

cs.CL2024★ 2 cited

LG AI Research & KAIST at EHRSQL 2024: Self-Training Large Language Models with Pseudo-Labeled Unanswerable Questions for a Reliable Text-to-SQL System on EHRs

Yongrae Jo, Seongyun Lee, Minju Seo +2

Text-to-SQL models are pivotal for making Electronic Health Records (EHRs) accessible to healthcare professionals without SQL knowledge. With the advancements in large language mod…

cs.CL2024★ 13 cited

ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models

Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan +1

The pace of scientific research, vital for improving human life, is complex, slow, and needs specialized expertise. Meanwhile, novel, impactful research often stems from both a dee…

cs.CL2024★ 10 cited

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

Soyeong Jeong, Jinheon Baek, Sukmin Cho +2

Retrieval-Augmented Large Language Models (LLMs), which incorporate the non-parametric knowledge from external knowledge bases into LLMs, have emerged as a promising approach to en…

cs.CL2024★ 2 cited

Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks

Minju Seo, Jinheon Baek, James Thorne +1

Despite large successes of recent language models on diverse tasks, they suffer from severe performance degeneration in low-resource settings with limited training data available.…