Search Results for author: Mujeen Sung

Found 12 papers, 10 papers with code

Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models

1 code implementation27 Jan 2024 Minbyul Jeong, Jiwoong Sohn, Mujeen Sung, Jaewoo Kang

To address challenges that still cannot be handled with the encoded knowledge of LLMs, various retrieval-augmented generation (RAG) methods have been developed by searching documents from the knowledge corpus and appending them unconditionally or selectively to the input of LLMs for generation.

Multiple-choice Question Answering +1

Optimizing Test-Time Query Representations for Dense Retrieval

1 code implementation25 May 2022 Mujeen Sung, Jungsoo Park, Jaewoo Kang, Danqi Chen, Jinhyuk Lee

In this paper, we introduce TOUR (Test-Time Optimization of Query Representations), which further optimizes instance-level query representations guided by signals from test-time retrieval results.

Contrastive Learning Open-Domain Question Answering +3

BERN2: an advanced neural biomedical named entity recognition and normalization tool

1 code implementation6 Jan 2022 Mujeen Sung, Minbyul Jeong, Yonghwa Choi, Donghyeon Kim, Jinhyuk Lee, Jaewoo Kang

In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e. g. diseases and drugs) from the ever-growing biomedical literature.

graph construction named-entity-recognition +2

Can Language Models be Biomedical Knowledge Bases?

1 code implementation EMNLP 2021 Mujeen Sung, Jinhyuk Lee, Sean Yi, Minji Jeon, Sungdong Kim, Jaewoo Kang

To this end, we create the BioLAMA benchmark, which is comprised of 49K biomedical factual knowledge triples for probing biomedical LMs.

Learning Dense Representations of Phrases at Scale

4 code implementations ACL 2021 Jinhyuk Lee, Mujeen Sung, Jaewoo Kang, Danqi Chen

Open-domain question answering can be reformulated as a phrase retrieval problem, without the need for processing documents on-demand during inference (Seo et al., 2019).

Open-Domain Question Answering Question Generation +4

Transferability of Natural Language Inference to Biomedical Question Answering

2 code implementations1 Jul 2020 Minbyul Jeong, Mujeen Sung, Gangwoo Kim, Donghyeon Kim, Wonjin Yoon, Jaehyo Yoo, Jaewoo Kang

We observe that BioBERT trained on the NLI dataset obtains better performance on Yes/No (+5. 59%), Factoid (+0. 53%), List type (+13. 58%) questions compared to performance obtained in a previous challenge (BioASQ 7B Phase B).

Natural Language Inference Question Answering +2

Biomedical Entity Representations with Synonym Marginalization

3 code implementations ACL 2020 Mujeen Sung, Hwisang Jeon, Jinhyuk Lee, Jaewoo Kang

In this way, we avoid the explicit pre-selection of negative samples from more than 400K candidates.

Adversarial Subword Regularization for Robust Neural Machine Translation

1 code implementation Findings of the Association for Computational Linguistics 2020 Jungsoo Park, Mujeen Sung, Jinhyuk Lee, Jaewoo Kang

Exposing diverse subword segmentations to neural machine translation (NMT) models often improves the robustness of machine translation as NMT models can experience various subword candidates.

Machine Translation NMT +1

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