Papers with Knowledge-intensive tasks
ReadTwice: Reading Very Large Documents with Memories (2021.naacl-main)
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| Challenge: | Existing approaches to model long-range dependencies in text are limited to 512 tokens . however, the amount of compute in attention depends quadratically on the number of tokens in an input text passage. |
| Approach: | They propose a technique that summarises text into a memory table to be used in a second read of the text. |
| Outcome: | The proposed method outperforms models of comparable size on several question answering datasets and sets a new state of the art on the NarrativeQA task, with questions about entire books. |
Empowering Small-Scale Knowledge Graphs: A Strategy of Leveraging General-Purpose Knowledge Graphs for Enriched Embeddings (2024.lrec-main)
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| Challenge: | Existing approaches to augment LLMs with Knowledge Graphs (KGs) Knowledge-intensive tasks are prone to errors and require a large amount of knowledge to be understood. |
| Approach: | They propose a framework for augmenting LLMs through Knowledge Graphs (KGs) they propose KGs can be used to enhance performance in knowledge-intensive tasks . |
| Outcome: | Experimental results show that a small domain-specific KG can benefit from a performance boost in downstream tasks when linked to a substantial general-purpose KG. |