2 citations · 5 across the 6 of their papers we have counts for
6 papers
Decomposition of surprisal: Unified computational model of ERP components in language processing
Jiaxuan Li, Richard Futrell
The functional interpretation of language-related ERP components has been a central debate in psycholinguistics for decades. We advance an information-theoretic model of human lang…
An information-theoretic model of shallow and deep language comprehension
Jiaxuan Li, Richard Futrell
A large body of work in psycholinguistics has focused on the idea that online language comprehension can be shallow or `good enough': given constraints on time or available computa…
Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific Experts
Jiaxuan Li, Duc Minh Vo, Hideki Nakayama
Bias mitigation in image classification has been widely researched, and existing methods have yielded notable results. However, most of these methods implicitly assume that a given…
Counterfactual reasoning: Testing language models' understanding of hypothetical scenarios
Jiaxuan Li, Lang Yu, Allyson Ettinger
Current pre-trained language models have enabled remarkable improvements in downstream tasks, but it remains difficult to distinguish effects of statistical correlation from more s…
A unified information-theoretic model of EEG signatures of human language processing
Jiaxuan Li, Richard Futrell
We advance an information-theoretic model of human language processing in the brain, in which incoming linguistic input is processed at two levels, in terms of a heuristic interpre…
Counterfactual reasoning: Do language models need world knowledge for causal understanding?
Jiaxuan Li, Lang Yu, Allyson Ettinger
Current pre-trained language models have enabled remarkable improvements in downstream tasks, but it remains difficult to distinguish effects of statistical correlation from more s…