Search Results for author: Yizhong Wang

Found 20 papers, 14 papers with code

TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering

1 code implementation21 Mar 2023 Yushi Hu, Benlin Liu, Jungo Kasai, Yizhong Wang, Mari Ostendorf, Ranjay Krishna, Noah A. Smith

We introduce TIFA (Text-to-Image Faithfulness evaluation with question Answering), an automatic evaluation metric that measures the faithfulness of a generated image to its text input via visual question answering (VQA).

Language Modelling Object Counting +3

HINT: Hypernetwork Instruction Tuning for Efficient Zero- & Few-Shot Generalisation

no code implementations20 Dec 2022 Hamish Ivison, Akshita Bhagia, Yizhong Wang, Hannaneh Hajishirzi, Matthew Peters

By converting instructions into modules, HINT models can effectively disregard the length of instructions and few-shot example inputs in terms of compute usage.

Self-Instruct: Aligning Language Model with Self Generated Instructions

8 code implementations20 Dec 2022 Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi

Applying our method to vanilla GPT3, we demonstrate a 33% absolute improvement over the original model on Super-NaturalInstructions, on par with the performance of InstructGPT_001, which is trained with private user data and human annotations.

Instruction Following Language Modelling

One Embedder, Any Task: Instruction-Finetuned Text Embeddings

1 code implementation19 Dec 2022 Hongjin Su, Weijia Shi, Jungo Kasai, Yizhong Wang, Yushi Hu, Mari Ostendorf, Wen-tau Yih, Noah A. Smith, Luke Zettlemoyer, Tao Yu

Our analysis suggests that INSTRUCTOR is robust to changes in instructions, and that instruction finetuning mitigates the challenge of training a single model on diverse datasets.

Information Retrieval Learning Word Embeddings +3

Automated Lay Language Summarization of Biomedical Scientific Reviews

1 code implementation23 Dec 2020 Yue Guo, Wei Qiu, Yizhong Wang, Trevor Cohen

Health literacy has emerged as a crucial factor in making appropriate health decisions and ensuring treatment outcomes.

Data Augmentation

LiveQA: A Question Answering Dataset over Sports Live

2 code implementations CCL 2020 Qianying Liu, Sicong Jiang, Yizhong Wang, Sujian Li

In this paper, we introduce LiveQA, a new question answering dataset constructed from play-by-play live broadcast.

Multiple-choice Question Answering

Do NLP Models Know Numbers? Probing Numeracy in Embeddings

1 code implementation IJCNLP 2019 Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, Matt Gardner

The ability to understand and work with numbers (numeracy) is critical for many complex reasoning tasks.

Question Answering

Machine Reading Comprehension: a Literature Review

no code implementations30 Jun 2019 Xin Zhang, An Yang, Sujian Li, Yizhong Wang

Machine reading comprehension aims to teach machines to understand a text like a human and is a new challenging direction in Artificial Intelligence.

Machine Reading Comprehension

Toward Fast and Accurate Neural Discourse Segmentation

1 code implementation EMNLP 2018 Yizhong Wang, Sujian Li, Jingfeng Yang

Discourse segmentation, which segments texts into Elementary Discourse Units, is a fundamental step in discourse analysis.

Discourse Segmentation

Bag-of-Words as Target for Neural Machine Translation

1 code implementation ACL 2018 Shuming Ma, Xu sun, Yizhong Wang, Junyang Lin

However, most of the existing neural machine translation models only use one of the correct translations as the targets, and the other correct sentences are punished as the incorrect sentences in the training stage.

Machine Translation Translation

Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification

no code implementations ACL 2018 Yizhong Wang, Kai Liu, Jing Liu, wei he, Yajuan Lyu, Hua Wu, Sujian Li, Haifeng Wang

Machine reading comprehension (MRC) on real web data usually requires the machine to answer a question by analyzing multiple passages retrieved by search engine.

Machine Reading Comprehension Question Answering

DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

3 code implementations WS 2018 Wei He, Kai Liu, Jing Liu, Yajuan Lyu, Shiqi Zhao, Xinyan Xiao, Yu-An Liu, Yizhong Wang, Hua Wu, Qiaoqiao She, Xuan Liu, Tian Wu, Haifeng Wang

Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.

Machine Reading Comprehension

A Two-Stage Parsing Method for Text-Level Discourse Analysis

1 code implementation ACL 2017 Yizhong Wang, Sujian Li, Houfeng Wang

Previous work introduced transition-based algorithms to form a unified architecture of parsing rhetorical structures (including span, nuclearity and relation), but did not achieve satisfactory performance.

Dependency Parsing Document Summarization +2

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