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Found 5 papers, 2 papers with code
EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning
On average, EchoPrompt improves the Zero-shot-CoT performance of code-davinci-002 by 5% in numerical tasks and 13% in reading comprehension tasks.
Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors
Large language models (LLMs) are being applied as actors for sequential decision making tasks in domains such as robotics and games, utilizing their general world knowledge and planning abilities.
A Theoretically Grounded Benchmark for Evaluating Machine Commonsense
Preliminary results suggest that the benchmark is challenging even for advanced language representation models designed for discriminative CSR question answering tasks.
Impact of Pretraining Term Frequencies on Few-Shot Reasoning
Pretrained Language Models (LMs) have demonstrated ability to perform numerical reasoning by extrapolating from a few examples in few-shot settings.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
The remarkable success of pretrained language models has motivated the study of what kinds of knowledge these models learn during pretraining.
