7 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks
Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg
In-context Learning (ICL) is the ability of Large Language Models (LLMs) to perform new tasks when conditioned on prompts comprising a few task examples. However, ICL performance c…
Leveraging Code to Improve In-context Learning for Semantic Parsing
Ben Bogin, Shivanshu Gupta, Peter Clark +1
In-context learning (ICL) is an appealing approach for semantic parsing due to its few-shot nature and improved generalization. However, learning to parse to rare domain-specific l…
Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages
Shivanshu Gupta, Yoshitomo Matsubara, Ankit Chadha +1
While impressive performance has been achieved on the task of Answer Sentence Selection (AS2) for English, the same does not hold for languages that lack large labeled datasets. In…
Coverage-based Example Selection for In-Context Learning
Shivanshu Gupta, Matt Gardner, Sameer Singh
In-context learning (ICL), the ability of large language models to perform novel tasks by conditioning on a prompt with a few task examples, requires these examples to be informati…