5 citations · 9 across the 4 of their papers we have counts for
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cs.CL2023★ 5 cited
LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models
Chi Han, Qifan Wang, Hao Peng +4
Today's large language models (LLMs) typically train on short text segments (e.g., <4K tokens) due to the quadratic complexity of their Transformer architectures. As a result, thei…
cs.CL2023
Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality
Harman Singh, Pengchuan Zhang, Qifan Wang +4
Contrastively trained vision-language models have achieved remarkable progress in vision and language representation learning, leading to state-of-the-art models for various downst…
cs.CL2023★ 3 cited
Representation Deficiency in Masked Language Modeling
Yu Meng, Jitin Krishnan, Sinong Wang +6
Masked Language Modeling (MLM) has been one of the most prominent approaches for pretraining bidirectional text encoders due to its simplicity and effectiveness. One notable concer…