McCoy, R. Thomas
- Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve
2023/09/24 by R. Thomas McCoy, McCoy, R. Thomas, Shunyu Yao +7 · 13 voices · 21 citations
Computer Science · #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling #cs.AI #cs.CL
- Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference
2019/02/04 by McCoy, R. Thomas, Pavlick, Ellie, Linzen, Tal · 49 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- Modeling rapid language learning by distilling Bayesian priors into artificial neural networks
2023/05/24 by R. Thomas McCoy, McCoy, R. Thomas, Thomas L. Griffiths +1 · 2 voices · 8 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling #Neural Networks and Applications
- When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1
2024/10/02 by R. Thomas McCoy, McCoy, R. Thomas, Shunyu Yao +7 · 6 voices · 6 citations
Computer Science · #Semantic Web and Ontologies #Natural Language Processing Techniques
- How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN
2021/11/18 by McCoy, R. Thomas, Smolensky, Paul, Linzen, Tal +2 · 10 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks
2018/02/25 by R. Thomas McCoy, Robert Frank, McCoy, R. Thomas +3 · 5 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling #Speech and dialogue systems
- Neurocompositional computing: From the Central Paradox of Cognition to a new generation of AI systems
2022/05/02 by Paul Smolensky, R. Thomas McCoy, Smolensky, Paul +7 · 6 citations
Computer Science · #Cognitive Science and Mapping #Neural Networks and Applications #Topological and Geometric Data Analysis
- Universal linguistic inductive biases via meta-learning
2020/06/29 by McCoy, R. Thomas, Grant, Erin, Smolensky, Paul +2 · 4 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Does syntax need to grow on trees? Sources of hierarchical inductive\n bias in sequence-to-sequence networks
2020/01/10 by R. Thomas McCoy, McCoy, R. Thomas, Robert Frank +3 · 4 citations
Computer Science · Neuroscience · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Neural Networks and Applications #Neurobiology of Language and Bilingualism
- How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech
2023/01/26 by Aditya Yedetore, Yedetore, Aditya, Tal Linzen +5 · 4 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2.7 #J.4 #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling
- Probing What Different NLP Tasks Teach Machines about Function Word Comprehension
2019/04/25 by Najoung Kim, Kim, Najoung, Roma Patel +21 · 2 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling
- BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance
2019/11/07 by R. Thomas McCoy, McCoy, R. Thomas, Junghyun Min +3 · 2 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
- Picking BERT's Brain: Probing for Linguistic Dependencies in Contextualized Embeddings Using Representational Similarity Analysis
2020/11/24 by Lepori, Michael A., McCoy, R. Thomas · 2 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- Learning to Reason via Mixture-of-Thought for Logical Reasoning
2025/05/21 by Tong Zheng, Lichang Chen, Zheng, Tong +7 · 12 citations
Computer Science · #Logic, Reasoning, and Knowledge
- Bayes in the age of intelligent machines
2023/11/16 by Thomas L. Griffiths, Griffiths, Thomas L., Jian-Qiao Zhu +5 · 2 voices · 2 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Bayesian Modeling and Causal Inference #Neural Networks and Applications
- What Should Embeddings Embed? Autoregressive Models Represent Latent Generating Distributions
2024/06/06 by Liyi Zhang, Michael Y. Li, Zhang, Liyi +5 · 3 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2 #I.5 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Topic Modeling
- Deciphering the Factors Influencing the Efficacy of Chain-of-Thought: Probability, Memorization, and Noisy Reasoning
2024/07/01 by Prabhakar, Akshara, Griffiths, Thomas L., McCoy, R. Thomas · 3 citations
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
- Teasing Apart Architecture and Initial Weights as Sources of Inductive Bias in Neural Networks
2025/02/27 by Gianluca Bencomo, Max Gupta, Bencomo, Gianluca +7 · 1 voice · 3 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Machine Learning and Data Classification #Domain Adaptation and Few-Shot Learning
- Whither symbols in the era of advanced neural networks?
2025/08/07 by Thomas L. Griffiths, Brenden M. Lake, Griffiths, Thomas L. +7 · 4 voices · 2 citations
#cs.AI
- Syntactic Data Augmentation Increases Robustness to Inference Heuristics
2020/04/24 by Min, Junghyun, McCoy, R. Thomas, Das, Dipanjan +2 · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- modeLing: A Novel Dataset for Testing Linguistic Reasoning in Language Models
2024/06/24 by Nathan A. Chi, Teodor Malchev, Chi, Nathan A. +13 · 2 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling
- Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models
2025/05/16 by Han, Simeng, Dai, Howard, Xia, Stephen +7 · 2 citations
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
- Levels of Analysis for Large Language Models
2025/03/17 by Ku, Alexander, Campbell, Declan, Bai, Xuechunzi +10 · 1 citation
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
- The Structural Sources of Verb Meaning Revisited: Large Language Models Display Syntactic Bootstrapping
2025/08/17 by Xiaomeng Zhu, Zhu, Xiaomeng, R. Thomas McCoy +3 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
- Identifying and Mitigating the Influence of the Prior Distribution in Large Language Models
2025/04/17 by Liyi Zhang, Zhang, Liyi, Veniamin Veselovsky +5 · 1 citation
Computer Science · Medicine · #Topic Modeling #Explainable Artificial Intelligence (XAI) #Artificial Intelligence in Healthcare and Education