Kazuma Hashimoto

research

∙ 09/14/2023

Ambiguity-Aware In-Context Learning with Large Language Models

In-context learning (ICL) i.e. showing LLMs only a few task-specific dem...

0 Lingyu Gao, et al. ∙

research

∙ 05/19/2023

Exploring the Viability of Synthetic Query Generation for Relevance Prediction

Query-document relevance prediction is a critical problem in Information...

0 Aditi Chaudhary, et al. ∙

research

∙ 12/21/2022

How Does Beam Search improve Span-Level Confidence Estimation in Generative Sequence Labeling?

Text-to-text generation models have increasingly become the go-to soluti...

0 Kazuma Hashimoto, et al. ∙

research

∙ 09/29/2022

GROOT: Corrective Reward Optimization for Generative Sequential Labeling

Sequential labeling is a fundamental NLP task, forming the backbone of m...

0 Kazuma Hashimoto, et al. ∙

research

∙ 07/05/2022

Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control

Abstractive summarization systems leveraging pre-training language model...

0 Haopeng Zhang, et al. ∙

research

∙ 05/18/2022

Modeling Multi-hop Question Answering as Single Sequence Prediction

Fusion-in-decoder (Fid) (Izacard and Grave, 2020) is a generative questi...

3 Semih Yavuz, et al. ∙

research

∙ 05/17/2022

OneAligner: Zero-shot Cross-lingual Transfer with One Rich-Resource Language Pair for Low-Resource Sentence Retrieval

Aligning parallel sentences in multilingual corpora is essential to cura...

0 Tong Niu, et al. ∙

research

∙ 03/16/2022

Transforming Sequence Tagging Into A Seq2Seq Task

Pretrained, large, generative language models (LMs) have had great succe...

0 Karthik Raman, et al. ∙

research

∙ 03/14/2022

Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering

While both extractive and generative readers have been successfully appl...

4 Man Luo, et al. ∙

research

∙ 10/28/2021

Dense Hierarchical Retrieval for Open-Domain Question Answering

Dense neural text retrieval has achieved promising results on open-domai...

0 Ye Liu, et al. ∙

research

∙ 10/08/2021

Field Extraction from Forms with Unlabeled Data

We propose a novel framework to conduct field extraction from forms with...

6 Mingfei Gao, et al. ∙

research

∙ 09/17/2021

RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

Existing KBQA approaches, despite achieving strong performance on i.i.d....

8 Xi Ye, et al. ∙

research

∙ 06/08/2021

Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection

Pretrained Transformer-based models were reported to be robust in intent...

19 Jian-Guo Zhang, et al. ∙

research

∙ 04/26/2021

Focused Attention Improves Document-Grounded Generation

Document grounded generation is the task of using the information provid...

26 Shrimai Prabhumoye, et al. ∙

research

∙ 03/10/2021

Causal-aware Safe Policy Improvement for Task-oriented dialogue

The recent success of reinforcement learning's (RL) in solving complex t...

0 Govardana Sachithanandam Ramachandran, et al. ∙

research

∙ 12/28/2020

Neural Text Generation with Artificial Negative Examples

Neural text generation models conditioning on given input (e.g. machine ...

0 Keisuke Shirai, et al. ∙

research

∙ 10/25/2020

Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference

Intent detection is one of the core components of goal-oriented dialog s...

10 Jian-Guo Zhang, et al. ∙

research

∙ 10/24/2020

CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers

Dialogue state trackers have made significant progress on benchmark data...

2 Shiyang Li, et al. ∙

research

∙ 06/24/2020

A High-Quality Multilingual Dataset for Structured Documentation Translation

This paper presents a high-quality multilingual dataset for the document...

0 Kazuma Hashimoto, et al. ∙

research

∙ 06/17/2020

CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization

The COVID-19 global pandemic has resulted in international efforts to un...

11 Andre Esteva, et al. ∙

research

∙ 02/27/2020

Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT

There is an increasing amount of literature that claims the brittleness ...

0 Lichao Sun, et al. ∙

research

∙ 11/24/2019

Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering

Answering questions that require multi-hop reasoning at web-scale necess...

0 Akari Asai, et al. ∙

research

∙ 10/08/2019

Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking

Dialog State Tracking (DST) is a core component in task-oriented dialog ...

23 Jian-Guo Zhang, et al. ∙

research

∙ 09/10/2018

Multilingual Extractive Reading Comprehension by Runtime Machine Translation

Existing end-to-end neural network models for extractive Reading Compreh...

0 Akari Asai, et al. ∙

research

∙ 09/05/2018

Accelerated Reinforcement Learning for Sentence Generation by Vocabulary Prediction

A major obstacle in reinforcement learning-based sentence generation is ...

0 Kazuma Hashimoto, et al. ∙

research

∙ 02/08/2017

Neural Machine Translation with Source-Side Latent Graph Parsing

This paper presents a novel neural machine translation model which joint...

0 Kazuma Hashimoto, et al. ∙

research

∙ 11/05/2016

A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks

Transfer and multi-task learning have traditionally focused on either a ...

0 Kazuma Hashimoto, et al. ∙

research

∙ 07/01/2016

Domain Adaptation for Neural Networks by Parameter Augmentation

We propose a simple domain adaptation method for neural networks in a su...

0 Yusuke Watanabe, et al. ∙

research

∙ 03/19/2016

Tree-to-Sequence Attentional Neural Machine Translation

Most of the existing Neural Machine Translation (NMT) models focus on th...

0 Akiko Eriguchi, et al. ∙

research

∙ 03/19/2016

Adaptive Joint Learning of Compositional and Non-Compositional Phrase Embeddings

We present a novel method for jointly learning compositional and non-com...

0 Kazuma Hashimoto, et al. ∙

research

∙ 02/28/2015

Task-Oriented Learning of Word Embeddings for Semantic Relation Classification

We present a novel learning method for word embeddings designed for rela...

0 Kazuma Hashimoto, et al. ∙

Kazuma Hashimoto

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