Hangbo Bao
13 papers · 2019–2023 · 7 conferences · across top CS/AI conferences
Achievements
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🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13)
🌈
Renaissance Researcher
(6)
🌍
Conference Polyglot
(7)
🤝
Dynamic Duo
(13)
🔥
Unstoppable
(5)
💎
Century Club
(13)
📈
Trend Setter
Conferences
ACL (4)
ICLR (2)
IJCNLP (2)
NIPS (2)
CVPR (1)
EMNLP (1)
ICML (1)
Top co-authors
Research topics
Keywords
multimodal learning
(2)
knowledge distillation
(2)
transformer architecture
(2)
model compression
(2)
attention mechanism
(1)
question answering
(1)
text summarization
(1)
pseudo labeling
(1)
machine reading comprehension
(1)
text understanding
(1)
language model
(1)
vision language model
(1)
foundation model
(1)
vision-language model
(1)
transformer network
(1)
image-text retrieval
(1)
ciphertext computation
(1)
encrypted datum
(1)
model deployment
(1)
pre-trained language model
(1)
Papers
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks
CVPR 2023
Corrupted Image Modeling for Self-Supervised Visual Pre-Training
ICLR 2023
BEiT: BERT Pre-Training of Image Transformers
ICLR 2022
VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts
NIPS 2022
Attention Temperature Matters in Abstractive Summarization Distillation
ACL 2022
THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption
ACL 2022
Learning to Sample Replacements for ELECTRA Pre-Training
IJCNLP 2021
MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers
ACL 2021
Learning to Sample Replacements for ELECTRA Pre-Training
ACL 2021
MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers
IJCNLP 2021
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
ICML 2020
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
NIPS 2020
Inspecting Unification of Encoding and Matching with Transformer: A Case Study of Machine Reading Comprehension
EMNLP 2019