Wenhui Wang

Affiliations:
  • Microsoft Research, Beijing, China


According to our database1, Wenhui Wang authored at least 32 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Fine-tuning pretrained transformer encoders for sequence-to-sequence learning.
Int. J. Mach. Learn. Cybern., May, 2024

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.
CoRR, 2024

2023
When an Image is Worth 1, 024 x 1, 024 Words: A Case Study in Computational Pathology.
CoRR, 2023

Kosmos-2.5: A Multimodal Literate Model.
CoRR, 2023

LongNet: Scaling Transformers to 1, 000, 000, 000 Tokens.
CoRR, 2023

Kosmos-2: Grounding Multimodal Large Language Models to the World.
CoRR, 2023

Language Is Not All You Need: Aligning Perception with Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Magneto: A Foundation Transformer.
Proceedings of the International Conference on Machine Learning, 2023

Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
TorchScale: Transformers at Scale.
CoRR, 2022

Foundation Transformers.
CoRR, 2022

Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks.
CoRR, 2022

Language Models are General-Purpose Interfaces.
CoRR, 2022

VL-BEiT: Generative Vision-Language Pretraining.
CoRR, 2022

AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models.
CoRR, 2022

VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Distilled Dual-Encoder Model for Vision-Language Understanding.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts.
CoRR, 2021

s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning.
CoRR, 2021

InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Consistency Regularization for Cross-Lingual Fine-Tuning.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Adapt-and-Distill: Developing Small, Fast and Effective Pretrained Language Models for Domains.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training.
Proceedings of the 37th International Conference on Machine Learning, 2020

Harvesting and Refining Question-Answer Pairs for Unsupervised QA.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Cross-Lingual Natural Language Generation via Pre-Training.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Unified Language Model Pre-training for Natural Language Understanding and Generation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Ask Unanswerable Questions for Machine Reading Comprehension.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Inspecting Unification of Encoding and Matching with Transformer: A Case Study of Machine Reading Comprehension.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

2018
Multiway Attention Networks for Modeling Sentence Pairs.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
Gated Self-Matching Networks for Reading Comprehension and Question Answering.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017


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