6 papers
Replacing Training with Memory: Listwise Selection for Text-to-SQL
Yeonseok Jeong, Soyoung Yoon, Seongjun Lee +1
Modern Text-to-SQL systems often follow generate-execute-select pipelines, generating multiple candidate queries then selecting the best one. Listwise selection, by jointly compari…
R-SQL: Ranking Reward and Resampling for Text-to-SQL
Hojae Han, Yeonseok Jeong, Seung-won Hwang +2
Modern Text-to-SQL systems generate multiple candidate SQL queries and rank them to judge a final prediction. However, existing methods face two limitations. First, they often scor…
ECoRAG: Evidentiality-guided Compression for Long Context RAG
Yeonseok Jeong, Jinsu Kim, Dohyeon Lee +1
Large Language Models (LLMs) have shown remarkable performance in Open-Domain Question Answering (ODQA) by leveraging external documents through Retrieval-Augmented Generation (RAG…
From Token to Action: State Machine Reasoning to Mitigate Overthinking in Information Retrieval
Dohyeon Lee, Yeonseok Jeong, Seung-won Hwang
Chain-of-Thought (CoT) prompting enables complex reasoning in large language models (LLMs), including applications in information retrieval (IR). However, it often leads to overthi…
Agent-as-Judge for Factual Summarization of Long Narratives
Yeonseok Jeong, Minsoo Kim, Seung-won Hwang +1
Large Language Models (LLMs) have demonstrated near-human performance in summarization tasks based on traditional metrics such as ROUGE and BERTScore. However, these metrics do not…
On Monotonic Aggregation for Open-domain QA
Sang-eun Han, Yeonseok Jeong, Seung-won Hwang +1
Question answering (QA) is a critical task for speech-based retrieval from knowledge sources, by sifting only the answers without requiring to read supporting documents. Specifical…