Papers by Lena Ann Jäger

3 papers
Genre Matters: How Text Types Interact with Decoding Strategies and Lexical Predictors in Shaping Reading Behavior (2025.emnlp-main)

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Challenge: eMTeC is the first eye-tracking corpus of LLM-generated texts . it shows that text type strongly modulates cognitive effort during reading .
Approach: They use the first eye-tracking corpus of LLM-generated texts to study eye movements during reading and how decoding strategies interact with text types to shape reading behavior.
Outcome: The first eye-tracking corpus of LLM-generated texts shows that text type strongly modulates cognitive effort during reading and that word-level psycholinguistic effects vary systematically across genres.
Leveraging In-Context Learning for Political Bias Testing of LLMs (2025.acl-long)

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Challenge: Existing probing methods for evaluating LLMs with political questions have limited stability and are unreliable.
Approach: They propose to use human survey data as in-context examples to query LLMs with political questions to evaluate their potential biases.
Outcome: The proposed task improves the stability of question-based bias evaluation and may be used to compare instruction-tuned models to their base versions.
Modeling Bottom-up Information Quality during Language Processing (2025.emnlp-main)

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Challenge: Contemporary theories of language processing model language processing as integrating both top-down expectations and bottom-up inputs.
Approach: They propose an information-theoretic operationalization for the “quality” of bottom-up information as the mutual information between visual information and word identity.
Outcome: The proposed model compares reading times in English and Chinese in which words' information quality has been reduced by occluding their top or bottom half with full words.

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