8 citations · 10 across the 18 of their papers we have counts for
6 papers · 1 filter
Language Impairment as a Lens onto Large Language Models
Muxuan He, Wang Bill Zhu, Yue Chen +5
Although large language models (LLMs) encode language in highly distributed spaces, they remain vulnerable to focal disruptions---a phenomenon strikingly similar to how localized b…
Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions
Wang Bill Zhu, Tianqi Chen, Xinyan Velocity Yu +6
Cancer patients are increasingly turning to large language models (LLMs) for medical information, making it critical to assess how well these models handle complex, personalized qu…
Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions?
Wang Zhu, Ishika Singh, Yuan Huang +2
Data augmentation via back-translation is common when pretraining Vision-and-Language Navigation (VLN) models, even though the generated instructions are noisy. But: does that nois…
Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering
Wang Zhu, Jesse Thomason, Robin Jia
We train a language model (LM) to robustly answer multistep questions by generating and answering sub-questions. We propose Chain-of-Questions, a framework that trains a model to g…
Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems
Wang Zhu, Jesse Thomason, Robin Jia
For vision-and-language reasoning tasks, both fully connectionist, end-to-end methods and hybrid, neuro-symbolic methods have achieved high in-distribution performance. In which ou…
Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks
Wang Zhu, Peter Shaw, Tal Linzen +1
Neural network models often generalize poorly to mismatched domains or distributions. In NLP, this issue arises in particular when models are expected to generalize compositionally…