activity
20162022
most citedData Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

62 citations · 182 across the 22 of their papers we have counts for

collaborators

40 papers

cs.CL202222 cited

Mind's Eye: Grounded Language Model Reasoning through Simulation

Ruibo Liu, Jason Wei, Shixiang Shane Gu +5

Successful and effective communication between humans and AI relies on a shared experience of the world. By training solely on written text, current language models (LMs) miss the…

cs.CL202254 cited

Language Models are Multilingual Chain-of-Thought Reasoners

Freda Shi, Mirac Suzgun, Markus Freitag +9

We evaluate the reasoning abilities of large language models in multilingual settings. We introduce the Multilingual Grade School Math (MGSM) benchmark, by manually translating 250…

cs.CL20226 cited

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…

cs.CL2022

Robin: A Novel Online Suicidal Text Corpus of Substantial Breadth and Scale

Daniel DiPietro, Vivek Hazari, Soroush Vosoughi

Suicide is a major public health crisis. With more than 20,000,000 suicide attempts each year, the early detection of suicidal intent has the potential to save hundreds of thousand…

cs.CL2022

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…

cs.CL2022

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…