1 citations · 2 across the 3 of their papers we have counts for
3 papers
How to Get Your LLM to Generate Challenging Problems for Evaluation
Arkil Patel, Siva Reddy, Dzmitry Bahdanau
The pace of evolution of Large Language Models (LLMs) necessitates new approaches for rigorous and comprehensive evaluation. Traditional human annotation is increasingly impractica…
MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations
Arkil Patel, Satwik Bhattamishra, Siva Reddy +1
Humans possess a remarkable ability to assign novel interpretations to linguistic expressions, enabling them to learn new words and understand community-specific connotations. Howe…
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
Satwik Bhattamishra, Arkil Patel, Phil Blunsom +1
In order to understand the in-context learning phenomenon, recent works have adopted a stylized experimental framework and demonstrated that Transformers can learn gradient-based l…