Papers by Liangze Li

2 papers
Token Prediction as Implicit Classification to Identify LLM-Generated Text (2023.emnlp-main)

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Challenge: a novel approach for identifying large language models (LLMs) involved in text generation is proposed . instead of adding an additional classification layer, we reframe the classification task as a next-token prediction task .
Approach: They propose a novel approach for identifying large language models involved in text generation . instead of adding an additional classification layer, they reframe the task as a next-token prediction task .
Outcome: The proposed method performs exceptionally well in the text classification task . it can distinguish distinctive writing styles among various LLMs even without an explicit classifier.
Listener Model for the PhotoBook Referential Game with CLIPScores as Implicit Reference Chain (2023.acl-short)

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Challenge: PhotoBook is a collaborative dialogue game where two players receive private, partially-overlapping sets of images and resolve which images they have in common.
Approach: They propose a reference chain-free listener model that directly addresses the game’s predictive task, i.e., deciding whether an image is shared with partner.
Outcome: The proposed model outperforms baseline models by >17 points on unseen images/game themes.

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