6 citations · 6 across the 5 of their papers we have counts for
5 papers
Non-Linguistic Supervision for Contrastive Learning of Sentence Embeddings
Yiren Jian, Chongyang Gao, Soroush Vosoughi
Semantic representation learning for sentences is an important and well-studied problem in NLP. The current trend for this task involves training a Transformer-based sentence encod…
Contrastive Learning for Prompt-Based Few-Shot Language Learners
Yiren Jian, Chongyang Gao, Soroush Vosoughi
The impressive performance of GPT-3 using natural language prompts and in-context learning has inspired work on better fine-tuning of moderately-sized models under this paradigm. F…
Embedding Hallucination for Few-Shot Language Fine-tuning
Yiren Jian, Chongyang Gao, Soroush Vosoughi
Few-shot language learners adapt knowledge from a pre-trained model to recognize novel classes from a few-labeled sentences. In such settings, fine-tuning a pre-trained language mo…
MetaPix: Domain Transfer for Semantic Segmentation by Meta Pixel Weighting
Yiren Jian, Chongyang Gao
Training a deep neural model for semantic segmentation requires collecting a large amount of pixel-level labeled data. To alleviate the data scarcity problem presented in the real…
Direct Information Reweighted by Contact Templates: Improved RNA Contact Prediction by Combining Structural Features
Yiren Jian, Chen Zeng, Yunjie Zhao
It is acknowledged that co-evolutionary nucleotide-nucleotide interactions are essential for RNA structures and functions. Currently, direct coupling analysis (DCA) infers nucleoti…