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Eight things to know about large language models
The widespread public deployment of large language models (LLMs) in recent months has
prompted a wave of new attention and engagement from advocates, policymakers, and …
prompted a wave of new attention and engagement from advocates, policymakers, and …
Symbols and grounding in large language models
Large language models (LLMs) are one of the most impressive achievements of artificial
intelligence in recent years. However, their relevance to the study of language more broadly …
intelligence in recent years. However, their relevance to the study of language more broadly …
Challenging big-bench tasks and whether chain-of-thought can solve them
BIG-Bench (Srivastava et al., 2022) is a diverse evaluation suite that focuses on tasks
believed to be beyond the capabilities of current language models. Language models have …
believed to be beyond the capabilities of current language models. Language models have …
Reasoning or reciting? exploring the capabilities and limitations of language models through counterfactual tasks
The impressive performance of recent language models across a wide range of tasks
suggests that they possess a degree of abstract reasoning skills. Are these skills general …
suggests that they possess a degree of abstract reasoning skills. Are these skills general …
Grounding large language models in interactive environments with online reinforcement learning
Recent works successfully leveraged Large Language Models'(LLM) abilities to capture
abstract knowledge about world's physics to solve decision-making problems. Yet, the …
abstract knowledge about world's physics to solve decision-making problems. Yet, the …
Language models represent space and time
The capabilities of large language models (LLMs) have sparked debate over whether such
systems just learn an enormous collection of superficial statistics or a set of more coherent …
systems just learn an enormous collection of superficial statistics or a set of more coherent …
Emergent world representations: Exploring a sequence model trained on a synthetic task
Language models show a surprising range of capabilities, but the source of their apparent
competence is unclear. Do these networks just memorize a collection of surface statistics, or …
competence is unclear. Do these networks just memorize a collection of surface statistics, or …
[PDF][PDF] The platonic representation hypothesis
We argue that representations in AI models, particularly deep networks, are converging.
First, we survey many examples of convergence in the literature: over time and across …
First, we survey many examples of convergence in the literature: over time and across …
Is a picture worth a thousand words? delving into spatial reasoning for vision language models
Large language models (LLMs) and vision-language models (VLMs) have demonstrated
remarkable performance across a wide range of tasks and domains. Despite this promise …
remarkable performance across a wide range of tasks and domains. Despite this promise …
From task structures to world models: what do LLMs know?
In what sense does a large language model (LLM) have knowledge? We answer by
granting LLMs 'instrumental knowledge': knowledge gained by using next-word generation …
granting LLMs 'instrumental knowledge': knowledge gained by using next-word generation …