17 citations · 17 across the 8 of their papers we have counts for
5 papers · 1 filter
Lost at the Beginning of Reasoning
Baohao Liao, Xinyi Chen, Sara Rajaee +5
Recent advancements in large language models (LLMs) have significantly advanced complex reasoning capabilities, particularly through extended chain-of-thought (CoT) reasoning that…
Mechanistic Interpretability Needs Philosophy
Iwan Williams, Ninell Oldenburg, Ruchira Dhar +6
Mechanistic interpretability (MI) aims to explain how neural networks work by uncovering their underlying mechanisms. As the field grows in influence, it is increasingly important…
Defining Knowledge: Bridging Epistemology and Large Language Models
Constanza Fierro, Ruchira Dhar, Filippos Stamatiou +2
Knowledge claims are abundant in the literature on large language models (LLMs); but can we say that GPT-4 truly "knows" the Earth is round? To address this question, we review sta…
From Words to Worlds: Compositionality for Cognitive Architectures
Ruchira Dhar, Anders Søgaard
Large language models (LLMs) are very performant connectionist systems, but do they exhibit more compositionality? More importantly, is that part of why they perform so well? We pr…
Word Order and World Knowledge
Qinghua Zhao, Vinit Ravishankar, Nicolas Garneau +1
Word order is an important concept in natural language, and in this work, we study how word order affects the induction of world knowledge from raw text using language models. We u…