Michihiro Yasunaga

research

∙ 07/27/2023

Med-Flamingo: a Multimodal Medical Few-shot Learner

Medicine, by its nature, is a multifaceted domain that requires the synt...

0 Michael Moor, et al. ∙

research

∙ 05/27/2023

Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models

Language models have been shown to exhibit positive scaling, where perfo...

0 Yuhui Zhang, et al. ∙

research

∙ 02/17/2023

Med-EASi: Finely Annotated Dataset and Models for Controllable Simplification of Medical Texts

Automatic medical text simplification can assist providers with patient-...

1 Chandrayee Basu, et al. ∙

research

∙ 02/08/2023

Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

Spurred by advancements in scale, large language models (LLMs) have demo...

10 Chengwei Qin, 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

∙ 01/28/2023

Zero-shot causal learning

Predicting how different interventions will causally affect a specific i...

10 Hamed Nilforoshan, et al. ∙

research

∙ 11/22/2022

Retrieval-Augmented Multimodal Language Modeling

Recent multimodal models such as DALL-E and CM3 have achieved remarkable...

28 Michihiro Yasunaga, et al. ∙

research

∙ 11/16/2022

Holistic Evaluation of Language Models

Language models (LMs) are becoming the foundation for almost all major l...

21 Percy Liang, et al. ∙

research

∙ 10/17/2022

Deep Bidirectional Language-Knowledge Graph Pretraining

Pretraining a language model (LM) on text has been shown to help various...

4 Michihiro Yasunaga, et al. ∙

research

∙ 05/23/2022

VQA-GNN: Reasoning with Multimodal Semantic Graph for Visual Question Answering

Visual understanding requires seamless integration between recognition a...

12 Yanan Wang, et al. ∙

research

∙ 03/29/2022

LinkBERT: Pretraining Language Models with Document Links

Language model (LM) pretraining can learn various knowledge from text co...

18 Michihiro Yasunaga, et al. ∙

research

∙ 01/21/2022

GreaseLM: Graph REASoning Enhanced Language Models for Question Answering

Answering complex questions about textual narratives requires reasoning ...

1 Xikun Zhang, et al. ∙

research

∙ 12/09/2021

Extending the WILDS Benchmark for Unsupervised Adaptation

Machine learning systems deployed in the wild are often trained on a sou...

17 Shiori Sagawa, et al. ∙

research

∙ 09/14/2021

LM-Critic: Language Models for Unsupervised Grammatical Error Correction

Training a model for grammatical error correction (GEC) requires a set o...

12 Michihiro Yasunaga, et al. ∙

research

∙ 06/11/2021

Break-It-Fix-It: Unsupervised Learning for Program Repair

We consider repair tasks: given a critic (e.g., compiler) that assesses ...

10 Michihiro Yasunaga, et al. ∙

research

∙ 04/13/2021

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering

The problem of answering questions using knowledge from pre-trained lang...

15 Michihiro Yasunaga, et al. ∙

research

∙ 12/14/2020

WILDS: A Benchmark of in-the-Wild Distribution Shifts

Distribution shifts can cause significant degradation in a broad range o...

11 Pang Wei Koh, et al. ∙

research

∙ 05/20/2020

Graph-based, Self-Supervised Program Repair from Diagnostic Feedback

We consider the problem of learning to repair programs from diagnostic f...

0 Michihiro Yasunaga, et al. ∙

research

∙ 10/30/2019

A Neural Topic-Attention Model for Medical Term Abbreviation Disambiguation

Automated analysis of clinical notes is attracting increasing attention....

0 Irene Li, et al. ∙

research

∙ 09/11/2019

CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

We present CoSQL, a corpus for building cross-domain, general-purpose da...

39 Tao Yu, et al. ∙

research

∙ 09/04/2019

ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks

Scientific article summarization is challenging: large, annotated corpor...

0 Michihiro Yasunaga, et al. ∙

research

∙ 09/04/2019

ScisummNet: A Large Annotated Dataset and Content-Impact Models for Scientific Paper Summarization with Citation Networks

Scientific article summarization is challenging: large, annotated corpor...

0 Michihiro Yasunaga, et al. ∙

research

∙ 09/02/2019

The CL-SciSumm Shared Task 2018: Results and Key Insights

This overview describes the official results of the CL-SciSumm Shared Ta...

0 Kokil Jaidka, et al. ∙

research

∙ 07/23/2019

Overview and Results: CL-SciSumm Shared Task 2019

The CL-SciSumm Shared Task is the first medium-scale shared task on scie...

0 Muthu Kumar Chandrasekaran, et al. ∙

research

∙ 06/05/2019

SParC: Cross-Domain Semantic Parsing in Context

We present SParC, a dataset for cross-domainSemanticParsing inContext th...

0 Tao Yu, et al. ∙

research

∙ 02/16/2019

TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts

Scientific documents rely on both mathematics and text to communicate id...

8 Michihiro Yasunaga, et al. ∙

research

∙ 10/11/2018

SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task

Most existing studies in text-to-SQL tasks do not require generating com...

0 Tao Yu, et al. ∙

research

∙ 09/24/2018

Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

We present Spider, a large-scale, complex and cross-domain semantic pars...

2 Tao Yu, et al. ∙

research

∙ 05/13/2018

Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering

Coreference resolution aims to identify in a text all mentions that refe...

0 Rui Zhang, et al. ∙

research

∙ 11/14/2017

Robust Multilingual Part-of-Speech Tagging via Adversarial Training

Adversarial training (AT) is a powerful regularization method for neural...

0 Michihiro Yasunaga, et al. ∙

research

∙ 06/20/2017

Graph-based Neural Multi-Document Summarization

We propose a neural multi-document summarization (MDS) system that incor...

0 Michihiro Yasunaga, et al. ∙

Michihiro Yasunaga

Featured Co-authors