12 citations · 12 across the 18 of their papers we have counts for
6 papers · 1 filter
Understanding When Tree of Thoughts Succeeds: Larger Models Excel in Generation, Not Discrimination
Qiqi Chen, Xinpeng Wang, Philipp Mondorf +2
Tree of Thoughts (ToT) is a reasoning strategy for Large Language Models (LLMs) that employs a generator to suggest reasoning steps and a discriminator to decide which steps to imp…
Circuit Compositions: Exploring Modular Structures in Transformer-Based Language Models
Philipp Mondorf, Sondre Wold, Barbara Plank
A fundamental question in interpretability research is to what extent neural networks, particularly language models, implement reusable functions through subnetworks that can be co…
LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks
Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi +17
There is an increasing trend towards evaluating NLP models with LLMs instead of human judgments, raising questions about the validity of these evaluations, as well as their reprodu…
Liar, Liar, Logical Mire: A Benchmark for Suppositional Reasoning in Large Language Models
Philipp Mondorf, Barbara Plank
Knights and knaves problems represent a classic genre of logical puzzles where characters either tell the truth or lie. The objective is to logically deduce each character's identi…
Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models -- A Survey
Philipp Mondorf, Barbara Plank
Large language models (LLMs) have recently shown impressive performance on tasks involving reasoning, leading to a lively debate on whether these models possess reasoning capabilit…
Comparing Inferential Strategies of Humans and Large Language Models in Deductive Reasoning
Philipp Mondorf, Barbara Plank
Deductive reasoning plays a pivotal role in the formulation of sound and cohesive arguments. It allows individuals to draw conclusions that logically follow, given the truth value…