Papers with generalisation ability
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning (P19-1)
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| Challenge: | Encoder-decoder models for unsupervised sentence representation learning discard decoder after training . decoded sentences are often used to make better predictions of words in a given sentence . |
| Approach: | They propose two types of decoding functions whose inverse can be easily derived without expensive inverse calculation. |
| Outcome: | The proposed models can learn good representations from encoders and decoders without expensive calculations. |
Blackbird language matrices (BLM), a new task for rule-like generalization in neural networks: Can Large Language Models pass the test? (2023.findings-emnlp)
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| Challenge: | Existing methods to evaluate large language models for generalization lack generalization ability . current methods for evaluating LLMs are based on tests of human intelligence . |
| Approach: | They propose to use a language task to evaluate large language models' generalisation ability . they propose to ask LLMs to solve simple variants of the RAVEN IQ test . |
| Outcome: | The proposed task can be used to evaluate the generalisation ability of large language models . it shows that current generative models can handle the task in the sense that they understand instructions . |