activity
20212026
collaborators

7 papers

cs.AI2026

Similarity All The Way Up: Multilingual Generalization in LLMs Relies on Language-Level Similarity Structures

Supantho Rakshit, Adele Goldberg, Henry Conklin

As Large Language Models (LLMs) grow more capable across diverse tasks, their (in)ability to generalize remains difficult to quantify and poorly understood beyond limited domains.…

cs.LG2026

Learning is Forgetting: LLM Training As Lossy Compression

Henry C. Conklin, Tom Hosking, Tan Yi-Chern +5

Despite the increasing prevalence of large language models (LLMs), we still have a limited understanding of how their representational spaces are structured. This limits our abilit…

cs.AI2026

Assessing the Effect of Cross-Domain Mapping on Creativity in Humans and Large Language Models

Qiawen Ella Liu, Marina Dubova, Henry Conklin +2

Creative ideas often arise by associating remote concepts. Can random associations reliably increase originality, and do they help humans and large language models (LLMs) in the sa…

cs.LG2025

Information Structure in Mappings: An Approach to Learning, Representation, and Generalisation

Henry Conklin

Despite the remarkable success of large large-scale neural networks, we still lack unified notation for thinking about and describing their representational spaces. We lack methods…

cs.CL2024

Representations as Language: An Information-Theoretic Framework for Interpretability

Henry Conklin, Kenny Smith

Large scale neural models show impressive performance across a wide array of linguistic tasks. Despite this they remain, largely, black-boxes - inducing vector-representations of t…

cs.CL2023

Anaphoric Structure Emerges Between Neural Networks

Nicholas Edwards, Hannah Rohde, Henry Conklin

Pragmatics is core to natural language, enabling speakers to communicate efficiently with structures like ellipsis and anaphora that can shorten utterances without loss of meaning.…

cs.CL2021

Meta-Learning to Compositionally Generalize

Henry Conklin, Bailin Wang, Kenny Smith +1

Natural language is compositional; the meaning of a sentence is a function of the meaning of its parts. This property allows humans to create and interpret novel sentences, general…