Ad-hoc Concept Forming in the Game Codenames as a Means for Evaluating Large Language Models
This provides a domain-specific evaluation tool for assessing LLMs in ad-hoc concept forming, but it is incremental as it applies existing methods to a new game-based benchmark.
The study used the game Codenames to benchmark large language models (LLMs) by having them generate clues and guess target words, revealing strategies and limitations in their linguistic and cognitive skills.
This study utilizes the game Codenames as a benchmarking tool to evaluate large language models (LLMs) with respect to specific linguistic and cognitive skills. LLMs play each side of the game, where one side generates a clue word covering several target words and the other guesses those target words. We designed various experiments by controlling the choice of words (abstract vs. concrete words, ambiguous vs. monosemic) or the opponent (programmed to be faster or slower in revealing words). Recent commercial and open-weight models were compared side-by-side to find out factors affecting their performance. The evaluation reveals details about their strategies, challenging cases, and limitations of LLMs.