Contents

• Large Language Models as General Pattern Machines (Jul 2023, added 7/18/23)
• Tart: A plug-and-play Transformer module for task-agnostic reasoning (Jun 2023, added 6/25/23)
• From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought (Jun 2023, added 6/24/23)
• Certified Reasoning with Language Models (Jun 2023, added 6/11/23)
• Tree of Thoughts: Deliberate Problem Solving with Large Language Models (May 2023, added 5/23/23)
• Comparing Machines and Children: Using Developmental Psychology Experiments to Assess the Strengths and Weaknesses of LaMDA Responses (May 2023, added 5/23/23)
• Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning (May 2022)
• Reasoning with Language Model Prompting: A Survey (Dec 2022)
• Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-thought (Jan 2023)
• Towards Reasoning in Large Language Models: A Survey
• Solving Quantitative Reasoning Problems with Language Models (Jul 2022)
• Why Does ChatGPT Fall Short in Answering Questions Faithfully? (Apr 2023, added 4/25/23)
• Is ChatGPT a Good Recommender? A Preliminary Study (Apr 2023)
• Are Emergent Abilities of Large Language Models a Mirage? (Apr 2023, added 5/1/23)

Large Language Models as General Pattern Machines (Jul 2023, added 7/18/23)

(link)

Cool paper that shows that LLMs are surprisingly good as pattern recognition machines: i.e., give them some kind of sequence, ask them to complete it, and they’ll get it right pretty often. This must be some basic, foundational way in which they work, because it shows up without any specific training.