Search Results for author: Xia Song

Found 26 papers, 15 papers with code

Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning

no code implementations26 Oct 2022 Barun Patra, Saksham Singhal, Shaohan Huang, Zewen Chi, Li Dong, Furu Wei, Vishrav Chaudhary, Xia Song

In this paper, we elaborate upon recipes for building multilingual representation models that are not only competitive with existing state-of-the-art models but are also more parameter efficient, thereby promoting better adoption in resource-constrained scenarios and practical applications.

Representation Learning

METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals

no code implementations13 Apr 2022 Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao

We present an efficient method of pretraining large-scale autoencoding language models using training signals generated by an auxiliary model.


Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators

1 code implementation ICLR 2022 Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song

We present a new framework AMOS that pretrains text encoders with an Adversarial learning curriculum via a Mixture Of Signals from multiple auxiliary generators.

Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training

1 code implementation EMNLP 2021 Bo Zheng, Li Dong, Shaohan Huang, Saksham Singhal, Wanxiang Che, Ting Liu, Xia Song, Furu Wei

We find that many languages are under-represented in recent cross-lingual language models due to the limited vocabulary capacity.

Language Modelling

DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual Encoders

1 code implementation25 Jun 2021 Shuming Ma, Li Dong, Shaohan Huang, Dongdong Zhang, Alexandre Muzio, Saksham Singhal, Hany Hassan Awadalla, Xia Song, Furu Wei

While pretrained encoders have achieved success in various natural language understanding (NLU) tasks, there is a gap between these pretrained encoders and natural language generation (NLG).

Abstractive Text Summarization Machine Translation +5

Language Scaling for Universal Suggested Replies Model

no code implementations NAACL 2021 Qianlan Ying, Payal Bajaj, Budhaditya Deb, Yu Yang, Wei Wang, Bojia Lin, Milad Shokouhi, Xia Song, Yang Yang, Daxin Jiang

Faced with increased compute requirements and low resources for language expansion, we build a single universal model for improving the quality and reducing run-time costs of our production system.

Continual Learning Cross-Lingual Transfer

COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

2 code implementations NeurIPS 2021 Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song

The first token-level task, Corrective Language Modeling, is to detect and correct tokens replaced by the auxiliary model, in order to better capture token-level semantics.

Contrastive Learning Language Modelling +1

Pretrain Knowledge-Aware Language Models

no code implementations1 Jan 2021 Corbin L Rosset, Chenyan Xiong, Minh Phan, Xia Song, Paul N. Bennett, Saurabh Tiwary

Rather, we simply signal the existence of entities to the input of the transformer in pretraining, with an entity-extended tokenizer; and at the output, with an additional entity prediction task.

Knowledge Probing Language Modelling +1

InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training

4 code implementations NAACL 2021 Zewen Chi, Li Dong, Furu Wei, Nan Yang, Saksham Singhal, Wenhui Wang, Xia Song, Xian-Ling Mao, He-Yan Huang, Ming Zhou

In this work, we present an information-theoretic framework that formulates cross-lingual language model pre-training as maximizing mutual information between multilingual-multi-granularity texts.

Contrastive Learning Cross-Lingual Transfer +1

Generic Intent Representation in Web Search

no code implementations24 Jul 2019 Hongfei Zhang, Xia Song, Chenyan Xiong, Corby Rosset, Paul N. Bennett, Nick Craswell, Saurabh Tiwary

This paper presents GEneric iNtent Encoder (GEN Encoder) which learns a distributed representation space for user intent in search.

Multi-Task Learning

An Axiomatic Approach to Regularizing Neural Ranking Models

no code implementations15 Apr 2019 Corby Rosset, Bhaskar Mitra, Chenyan Xiong, Nick Craswell, Xia Song, Saurabh Tiwary

The training of these models involve a search for appropriate parameter values based on large quantities of labeled examples.

Information Retrieval Retrieval

Towards Language Agnostic Universal Representations

no code implementations ACL 2019 Armen Aghajanyan, Xia Song, Saurabh Tiwary

When a bilingual student learns to solve word problems in math, we expect the student to be able to solve these problem in both languages the student is fluent in, even if the math lessons were only taught in one language.

MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

12 code implementations28 Nov 2016 Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, Tong Wang

The size of the dataset and the fact that the questions are derived from real user search queries distinguishes MS MARCO from other well-known publicly available datasets for machine reading comprehension and question-answering.

Benchmarking Machine Reading Comprehension +1

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