263 citations · 694 across the 35 of their papers we have counts for
4 papers · 2 filters
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
Qinyuan Ye, Harvey Yiyun Fu, Xiang Ren +1
We investigate the predictability of large language model (LLM) capabilities: given records of past experiments using different model families, numbers of parameters, tasks, and nu…
Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering
Wang Zhu, Jesse Thomason, Robin Jia
We train a language model (LM) to robustly answer multistep questions by generating and answering sub-questions. We propose Chain-of-Questions, a framework that trains a model to g…
Estimating Large Language Model Capabilities without Labeled Test Data
Harvey Yiyun Fu, Qinyuan Ye, Albert Xu +2
Large Language Models (LLMs) have the impressive ability to perform in-context learning (ICL) from only a few examples, but the success of ICL varies widely from task to task. Thus…
SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples
Deqing Fu, Ameya Godbole, Robin Jia
Detecting negatives (such as non-entailment relationships, unanswerable questions, and false claims) is an important and challenging aspect of many natural language understanding t…