Papers by Simon Jenni

1 papers
MAGNET: Augmenting Generative Decoders with Representation Learning and Infilling Capabilities (2025.acl-long)

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Challenge: Decoder-only large language models are increasingly being adapted for bidirectional modeling . however, their reliance on causal attention restricts their effectiveness in tasks that require understanding of bidirectional context.
Approach: They propose a method to adapt decoder-only large language models to generate robust representations and infill missing text spans.
Outcome: The proposed method surpasses strong decoders on token-level and sentence-level representation learning tasks and generates contextually appropriate text infills without excessive repetition of words or phrases.

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