32 citations · 86 across the 16 of their papers we have counts for
23 papers · 1 filter
Hindsight: Posterior-guided training of retrievers for improved open-ended generation
Ashwin Paranjape, Omar Khattab, Christopher Potts +2
Many text generation systems benefit from using a retriever to retrieve passages from a textual knowledge corpus (e.g., Wikipedia) which are then provided as additional context to…
ReaSCAN: Compositional Reasoning in Language Grounding
Zhengxuan Wu, Elisa Kreiss, Desmond C. Ong +1
The ability to compositionally map language to referents, relations, and actions is an essential component of language understanding. The recent gSCAN dataset (Ruis et al. 2020, Ne…
Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking
Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush +6
We introduce Dynaboard, an evaluation-as-a-service framework for hosting benchmarks and conducting holistic model comparison, integrated with the Dynabench platform. Our platform e…
Identifying the Limits of Cross-Domain Knowledge Transfer for Pretrained Models
Zhengxuan Wu, Nelson F. Liu, Christopher Potts
There is growing evidence that pretrained language models improve task-specific fine-tuning not just for the languages seen in pretraining, but also for new languages and even non-…
Dynabench: Rethinking Benchmarking in NLP
Douwe Kiela, Max Bartolo, Yixin Nie +16
We introduce Dynabench, an open-source platform for dynamic dataset creation and model benchmarking. Dynabench runs in a web browser and supports human-and-model-in-the-loop datase…
DynaSent: A Dynamic Benchmark for Sentiment Analysis
Christopher Potts, Zhengxuan Wu, Atticus Geiger +1
We introduce DynaSent ('Dynamic Sentiment'), a new English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis. DynaSent combines naturally occurring…