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20112023
most citedWhat do you learn from context? Probing for sentence structure in contextualized word representations

139 citations · 635 across the 23 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CL2022★ 27 cited

Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models

Bernd Bohnet, Vinh Q. Tran, Pat Verga +19

Large language models (LLMs) have shown impressive results while requiring little or no direct supervision. Further, there is mounting evidence that LLMs may have potential in info…

cs.CL2022★ 10 cited

QAmeleon: Multilingual QA with Only 5 Examples

Priyanka Agrawal, Chris Alberti, Fantine Huot +6

The availability of large, high-quality datasets has been one of the main drivers of recent progress in question answering (QA). Such annotated datasets however are difficult and c…

cs.CL2022★ 5 cited

Query Refinement Prompts for Closed-Book Long-Form Question Answering

Reinald Kim Amplayo, Kellie Webster, Michael Collins +2

Large language models (LLMs) have been shown to perform well in answering questions and in producing long-form texts, both in few-shot closed-book settings. While the former can be…

cs.CL2022★ 54 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.CL2022★ 2 cited

Conditional Generation with a Question-Answering Blueprint

Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo +6

The ability to convey relevant and faithful information is critical for many tasks in conditional generation and yet remains elusive for neural seq-to-seq models whose outputs ofte…

cs.CL2022★ 2 cited

A Well-Composed Text is Half Done! Composition Sampling for Diverse Conditional Generation

Shashi Narayan, Gonçalo Simões, Yao Zhao +4

We propose Composition Sampling, a simple but effective method to generate diverse outputs for conditional generation of higher quality compared to previous stochastic decoding str…