8 papers · 1 filter
Disentangling Statistical Preemption from Entrenchment in Language Models' Avoidance of Overgeneralization
Yixuan Wang, Freda Shi, Kanishka Misra
How do learners avoid overgeneralizations such as Tom laughed me without explicit negative evidence? Constructionists have posited two proposals that describe indirect negative evi…
What's in a Name? Morphological Shortcuts by LLMs in Pharmacology
Kaijie Mo, Thomas Yang, Chantal Shaib +6
The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes domains. In the medical doma…
HERO'S JOURNEY: Testing Complex Rule Induction with Text Games
Anshun Asher Zheng, Kanishka Misra, David I. Beaver +1
We introduce HERO'S JOURNEY, a benchmark for rule induction in goal-directed episodic tasks, where agents must infer hidden rules from demonstrations and act on them through multi-…
Which course? Discourse! Teaching Discourse and Generation in the Era of LLMs
Junyi Jessy Li, Yang Janet Liu, Kanishka Misra +2
The field of NLP has undergone vast, continuous transformations over the past few years, sparking debates going beyond discipline boundaries. This begs important questions in educa…
Bears, all bears, and some bears. Language Constraints on Language Models' Inductive Inferences
Sriram Padmanabhan, Siyuan Song, Kanishka Misra
Language places subtle constraints on how we make inductive inferences. Developmental evidence by Gelman et al. (2002) has shown children (4 years and older) to differentiate among…
WUGNECTIVES: Novel Entity Inferences of Language Models from Discourse Connectives
Daniel Brubaker, William Sheffield, Junyi Jessy Li +1
The role of world knowledge has been particularly crucial to predict the discourse connective that marks the discourse relation between two arguments, with language models (LMs) be…
semantic-features: A User-Friendly Tool for Studying Contextual Word Embeddings in Interpretable Semantic Spaces
Jwalanthi Ranganathan, Rohan Jha, Kanishka Misra +1
We introduce semantic-features, an extensible, easy-to-use library based on Chronis et al. (2023) for studying contextualized word embeddings of LMs by projecting them into interpr…
On Language Models' Sensitivity to Suspicious Coincidences
Sriram Padmanabhan, Kanishka Misra, Kyle Mahowald +1
Humans are sensitive to suspicious coincidences when generalizing inductively over data, as they make assumptions as to how the data was sampled. This results in smaller, more spec…