Papers by Ondřej Cífka
Black-box language model explanation by context length probing (2023.acl-short)
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| Challenge: | *context length probing* is a new explanation technique for large language models . it tracks the predictions of a model as a function of the length of available context . |
| Approach: | They propose a method that tracks the predictions of a model as a function of the length of available context and allows to assign *differential importance scores* to different contexts. |
| Outcome: | The proposed method is model-agnostic and does not rely on access to model internals beyond token-level probabilities. |
Are BLEU and Meaning Representation in Opposition? (P18-1)
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| Challenge: | Empirical evaluation suggests that the better the translation quality, the worse the learned sentence representations serve in a wide range of classification and similarity tasks. |
| Approach: | They propose several variations of the attentive NMT architecture to bring this meeting point back . they propose to use a structured fixed-size representation of the input to produce static representations of input sentences. |
| Outcome: | The proposed architecture improves translation quality and performance in a range of tasks. |