Papers with Weight tying

2 papers
Revisiting Representation Degeneration Problem in Language Modeling (2020.findings-emnlp)

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Challenge: Language modeling is a fundamental task in natural language processing, applications include machine translation, image captioning and speech recognition.
Approach: They propose a cosine regularization method to solve the representation degeneration problem by analyzing the limitations of the proposed method and then propose an alternative regularization technique to tackle the problem.
Outcome: The proposed method is effective in language modeling and image captioning.
Weight Tying Biases Token Embeddings Towards the Output Space (2026.findings-acl)

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Challenge: Weight tying is a common practice in language model design, but its impact on learning embedding space remains unclear.
Approach: They show that weight tying optimizes the embedding matrix for output prediction . they also show that tied embeddable matrices align more closely with output embedders .
Outcome: The proposed weight tying approach harms performance at scale and has implications for training smaller LLMs.

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