5 papers
LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs
Jihwan Kim, Nikhil Parthasarathy, Danfeng Qin +5
The fundamental challenge in scaling Video Large Language Models (Video LLMs) to long-form video lies in managing the explosion of visual-token context length. Existing strategies…
Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Method
Taehee Kim, Seungbin Yang, Jihwan Kim +1
Retrieving relevant tables from extensive databases for a given natural language query is essential for accurately answering questions in tasks such as text-to-SQL. Existing table…
LiveWeb-IE: A Benchmark For Online Web Information Extraction
Seungbin Yang, Jihwan Kim, Jaemin Choi +4
Web information extraction (WIE) is the task of automatically extracting data from web pages, offering high utility for various applications. The evaluation of WIE systems has trad…
Expanding Foundational Language Capabilities in Open-Source LLMs through a Korean Case Study
Junghwan Lim, Gangwon Jo, Sungmin Lee +16
We introduce Llama-3-Motif, a language model consisting of 102 billion parameters, specifically designed to enhance Korean capabilities while retaining strong performance in Englis…
Motif 2.6B Technical Report
Junghwan Lim, Sungmin Lee, Dongseok Kim +22
Recent advancements in Large Language Models (LLMs) have revolutionized artificial intelligence, yet developing an effective foundational LLM that balances high performance with co…