b'Minjoon Seo'

research

∙ 07/20/2023

FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets

Evaluation of Large Language Models (LLMs) is challenging because aligni...

0 Seonghyeon Ye, et al. ∙

research

∙ 07/05/2023

Zero-Shot Dense Video Captioning by Jointly Optimizing Text and Moment

Dense video captioning, a task of localizing meaningful moments and gene...

0 Yongrae Jo, et al. ∙

research

∙ 06/12/2023

Gradient Ascent Post-training Enhances Language Model Generalization

In this work, we empirically show that updating pretrained LMs (350M, 1....

0 Dongkeun Yoon, et al. ∙

research

∙ 05/31/2023

A Bayesian Perspective On Training Data Attribution

Training data attribution (TDA) techniques find influential training dat...

1 Elisa Nguyen, et al. ∙

research

∙ 05/27/2023

Continually Updating Generative Retrieval on Dynamic Corpora

Generative retrieval has recently been gaining a lot of attention from t...

0 Soyoung Yoon, et al. ∙

research

∙ 05/24/2023

Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis

Large Language Models (LLMs) have demonstrated great capabilities in sol...

0 Sohee Yang, et al. ∙

research

∙ 05/23/2023

The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning

Large Language Models (LLMs) have shown enhanced capabilities of solving...

0 Seungone Kim, et al. ∙

research

∙ 05/23/2023

Effortless Integration of Memory Management into Open-Domain Conversation Systems

Open-domain conversation systems integrate multiple conversation skills ...

0 Eunbi Choi, et al. ∙

research

∙ 05/23/2023

Aligning Large Language Models through Synthetic Feedback

Aligning large language models (LLMs) to human values has become increas...

0 Sungdong Kim, et al. ∙

research

∙ 02/28/2023

In-Context Instruction Learning

Instruction learning of Large Language Models (LLMs) has enabled zero-sh...

0 Seonghyeon Ye, et al. ∙

research

∙ 02/07/2023

Exploring the Benefits of Training Expert Language Models over Instruction Tuning

Recently, Language Models (LMs) instruction-tuned on multiple tasks, als...

8 Joel Jang, et al. ∙

research

∙ 01/30/2023

REPLUG: Retrieval-Augmented Black-Box Language Models

We introduce REPLUG, a retrieval-augmented language modeling framework t...

7 Weijia Shi, et al. ∙

research

∙ 01/27/2023

Semi-Parametric Video-Grounded Text Generation

Efficient video-language modeling should consider the computational cost...

0 Sungdong Kim, et al. ∙

research

∙ 11/03/2022

Data-efficient End-to-end Information Extraction for Statistical Legal Analysis

Legal practitioners often face a vast amount of documents. Lawyers, for ...

0 Wonseok Hwang, et al. ∙

research

∙ 10/25/2022

Towards standardizing Korean Grammatical Error Correction: Datasets and Annotation

Research on Korean grammatical error correction (GEC) is limited compare...

2 Soyoung Yoon, et al. ∙

research

∙ 10/06/2022

Retrieval of Soft Prompt Enhances Zero-Shot Task Generalization

During zero-shot inference with language models (LMs), using hard prompt...

8 Seonghyeon Ye, et al. ∙

research

∙ 10/06/2022

Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners

Meta-training, which fine-tunes the language model (LM) on various downs...

10 Seonghyeon Ye, et al. ∙

research

∙ 10/05/2022

Contextualized Generative Retrieval

The text retrieval task is mainly performed in two ways: the bi-encoder ...

0 Hyunji Lee, et al. ∙

research

∙ 10/04/2022

Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Pretrained Language Models (LMs) memorize a vast amount of knowledge dur...

0 Joel Jang, et al. ∙

research

∙ 09/26/2022

Can Large Language Models Truly Understand Prompts? A Case Study with Negated Prompts

Previous work has shown that there exists a scaling law between the size...

9 Joel Jang, et al. ∙

research

∙ 06/10/2022

A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction

The recent advances of deep learning have dramatically changed how machi...

0 Wonseok Hwang, et al. ∙

research

∙ 05/24/2022

Beyond Fact Verification: Comparing and Contrasting Claims on Contentious Topics

As the importance of identifying misinformation is increasing, many rese...

0 Miyoung Ko, et al. ∙

research

∙ 04/29/2022

TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models

Language Models (LMs) become outdated as the world changes; they often f...

13 Joel Jang, et al. ∙

research

∙ 04/27/2022

Generative Multi-hop Retrieval

Multi-hop retrieval is the task of retrieving a series of multiple docum...

0 Hyunji Lee, et al. ∙

research

∙ 02/23/2022

Semi-Structured Query Grounding for Document-Oriented Databases with Deep Retrieval and Its Application to Receipt and POI Matching

Semi-structured query systems for document-oriented databases have many ...

0 Geewook Kim, et al. ∙

research

∙ 10/11/2021

ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation

Video-text retrieval has many real-world applications such as media anal...

0 Aiden Seungjoon Lee, et al. ∙

research

∙ 10/07/2021

Towards Continual Knowledge Learning of Language Models

Large Language Models (LMs) are known to encode world knowledge in their...

0 Joel Jang, et al. ∙

research

∙ 04/16/2021

Cost-effective End-to-end Information Extraction for Semi-structured Document Images

A real-world information extraction (IE) system for semi-structured docu...

0 Wonseok Hwang, et al. ∙

research

∙ 04/15/2021

Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering

In open-domain question answering (QA), retrieve-and-read mechanism has ...

0 Sohee Yang, et al. ∙

research

∙ 01/01/2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...

15 Sewon Min, et al. ∙

research

∙ 10/21/2020

Is Retriever Merely an Approximator of Reader?

The state of the art in open-domain question answering (QA) relies on an...

0 Sohee Yang, et al. ∙

research

∙ 05/01/2020

Syntactic Question Abstraction and Retrieval for Data-Scarce Semantic Parsing

Deep learning approaches to semantic parsing require a large amount of l...

0 Wonseok Hwang, et al. ∙

research

∙ 05/01/2020

Spatial Dependency Parsing for 2D Document Understanding

Information Extraction (IE) for document images is often approached as a...

0 Wonseok Hwang, et al. ∙

research

∙ 11/07/2019

Contextualized Sparse Representation with Rectified N-Gram Attention for Open-Domain Question Answering

A sparse representation is known to be an effective means to encode prec...

0 Jinhyuk Lee, et al. ∙

research

∙ 10/22/2019

MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension

We present the results of the Machine Reading for Question Answering (MR...

0 Adam Fisch, et al. ∙

research

∙ 09/04/2019

Mixture Content Selection for Diverse Sequence Generation

Generating diverse sequences is important in many NLP applications such ...

0 Jaemin Cho, et al. ∙

research

∙ 06/13/2019

Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index

Existing open-domain question answering (QA) models are not suitable for...

0 Minjoon Seo, et al. ∙

research

∙ 02/04/2019

A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization

WikiSQL is the task of mapping a natural language question to a SQL quer...

0 Wonseok Hwang, et al. ∙

research

∙ 04/20/2018

Phrase-Indexed Question Answering: A New Challenge for Scalable Document Comprehension

The current trend of extractive question answering (QA) heavily relies o...

0 Minjoon Seo, et al. ∙

research

∙ 11/06/2017

Neural Speed Reading via Skim-RNN

Inspired by the principles of speed reading, we introduce Skim-RNN, a re...

0 Minjoon Seo, et al. ∙

research

∙ 06/13/2017

Zero-Shot Relation Extraction via Reading Comprehension

We show that relation extraction can be reduced to answering simple read...

0 Omer Levy, et al. ∙

research

∙ 02/07/2017

Question Answering through Transfer Learning from Large Fine-grained Supervision Data

We show that the task of question answering (QA) can significantly benef...

0 Sewon Min, et al. ∙

research

∙ 11/05/2016

Bidirectional Attention Flow for Machine Comprehension

Machine comprehension (MC), answering a query about a given context para...

0 Minjoon Seo, et al. ∙

research

∙ 06/14/2016

Query-Reduction Networks for Question Answering

In this paper, we study the problem of question answering when reasoning...

0 Minjoon Seo, et al. ∙

research

∙ 03/24/2016

A Diagram Is Worth A Dozen Images

Diagrams are common tools for representing complex concepts, relationshi...

0 Aniruddha Kembhavi, et al. ∙

Minjoon Seo

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