Martha Lewis
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Papers (14)
- Transformer See, Transformer Do: Copying as an Intermediate Step in Learning Analogical Reasoning cs.LG · 2026 · author #4
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models cs.CL · 2022 · author #253
- Compositionality for Recursive Neural Networks cs.CL · 2019 · author #1
- Proceedings of the 2018 Workshop on Compositional Approaches in Physics, NLP, and Social Sciences cs.CL · 2018 · author #1
- Interacting Conceptual Spaces I : Grammatical Composition of Concepts cs.LO · 2017 · author #4
- Compositional Distributional Cognition cs.AI · 2016 · author #3
- Proceedings of the 2016 Workshop on Semantic Spaces at the Intersection of NLP, Physics and Cognitive Science cs.CL · 2016 · author #2
- Harmonic Grammar in a DisCo Model of Meaning cs.AI · 2016 · author #1
- Emerging Dimension Weights in a Conceptual Spaces Model of Concept Combination cs.AI · 2016 · author #1
- The Utility of Hedged Assertions in the Emergence of Shared Categorical Labels cs.AI · 2016 · author #1
- A Label Semantics Approach to Linguistic Hedges cs.AI · 2016 · author #1
- Concept Generation in Language Evolution cs.AI · 2016 · author #1
- Graded Entailment for Compositional Distributional Semantics cs.CL · 2016 · author #3
- A Compositional Explanation of the Pet Fish Phenomenon cs.AI · 2015 · author #2
Mentions
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Frequent Coauthors
- Bob Coecke 6 shared papers
- Jonathan Lawry 4 shared papers
- Dan Marsden 2 shared papers
- Aarohi Srivastava 1 shared papers
- Abhinav Rastogi 1 shared papers
- Abhishek Rao 1 shared papers
- Abu Awal Md Shoeb 1 shared papers
- Abubakar Abid 1 shared papers
- Adam Fisch 1 shared papers
- Adam R. Brown 1 shared papers
- Adam Santoro 1 shared papers
- Aditya Gupta 1 shared papers
- Adri\`a Garriga-Alonso 1 shared papers
- Agnieszka Kluska 1 shared papers
- Aitor Lewkowycz 1 shared papers
- Akshat Agarwal 1 shared papers
- Alethea Power 1 shared papers
- Alexander W. Kocurek 1 shared papers
- Alex Ray 1 shared papers
- Alex Warstadt 1 shared papers