You Can't Fight in Here! This is BBS!
Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models can inform important questions in the language sciences. Just as they are about to part ways until they meet again, 25 of their closest friends show up -- from linguistics, neuroscience, cognitive science, psychology, philosophy, and computer science. We use this discussion to highlight what we see as some common underlying issues: the String Statistics Strawman (the mistaken idea that LMs can't be linguistically competent or interesting because they, like their Markov model predecessors, are statistical models that learn from strings) and the As Good As it Gets Assumption (the idea that LM research as it stands in 2026 is the limit of what it can tell us about linguistics). We clarify the role of LM-based work for scientific insights into human language and advocate for a more expansive research program for the language sciences in the AI age, one that takes on the commentators' concerns in order to produce a better and more robust science of both human language and of LMs.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
DareFightingICE Competition: A Fighting Game Sound Design and AI Competition
This paper presents a new competition -- at the 2022 IEEE Conference on Games (CoG) -- called DareFightingICE Competition. The competition has two tracks: a sound design track and an AI track. The game platform for this …
Fight Detection from Still Images in the Wild
Detecting fights from still images shared on social media is an important task required to limit the distribution of violent scenes in order to prevent their negative effects. For this reason, in this study, we address t…
An Imitative Reinforcement Learning Framework for Autonomous Dogfight
Unmanned Combat Aerial Vehicle (UCAV) dogfight, which refers to a fight between two or more UCAVs usually at close quarters, plays a decisive role on the aerial battlefields. With the evolution of artificial intelligence…
Imitation Learningreinforcement-learningReinforcement LearningInstilling Organisational Values in Firefighters through Simulation-Based Training
In firefighting and other emergency operations, decisions made under pressure carry profound ethical weight and can significantly impact incident outcomes and firefighter safety. Traditional training methods, while found…
Harfang3D Dog-Fight Sandbox: A Reinforcement Learning Research Platform for the Customized Control Tasks of Fighter Aircrafts
The advent of deep learning (DL) gave rise to significant breakthroughs in Reinforcement Learning (RL) research. Deep Reinforcement Learning (DRL) algorithms have reached super-human level skills when applied to vision-b…
Atari GamesDecision MakingDeep Reinforcement Learningreinforcement-learning+2