82 citations · 320 across the 14 of their papers we have counts for
7 papers · 1 filter
Ask Me Anything: A simple strategy for prompting language models
Simran Arora, Avanika Narayan, Mayee F. Chen +6
Large language models (LLMs) transfer well to new tasks out-of-the-box simply given a natural language prompt that demonstrates how to perform the task and no additional training.…
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions
Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu +3
Commercial ML APIs offered by providers such as Google, Amazon and Microsoft have dramatically simplified ML adoption in many applications. Numerous companies and academics pay to…
LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning
Neel Guha, Daniel E. Ho, Julian Nyarko +1
Can foundation models be guided to execute tasks involving legal reasoning? We believe that building a benchmark to answer this question will require sustained collaborative effort…
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval
Megan Leszczynski, Daniel Y. Fu, Mayee F. Chen +1
Entity retrieval--retrieving information about entity mentions in a query--is a key step in open-domain tasks, such as question answering or fact checking. However, state-of-the-ar…
Reasoning over Public and Private Data in Retrieval-Based Systems
Simran Arora, Patrick Lewis, Angela Fan +2
Users and organizations are generating ever-increasing amounts of private data from a wide range of sources. Incorporating private data is important to personalize open-domain appl…
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
Sabri Eyuboglu, Maya Varma, Khaled Saab +5
Machine learning models that achieve high overall accuracy often make systematic errors on important subsets (or slices) of data. Identifying underperforming slices is particularly…