Papers with GPT-3.5 models
Entity Tracking in Language Models (2023.acl-long)
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| Challenge: | Existing studies on the ability of large language models to track discourse entities have not been conducted. |
| Approach: | They propose to investigate whether large language models can track entities . they first investigate whether Flan-T5, GPT-3 and GPT-3.5 can track the state of entities based on an English description of the initial state and a series of state-changing operations. |
| Outcome: | The proposed task investigates whether language models can track entities based on language descriptions and state-changing operations. |
Prompted Opinion Summarization with GPT-3.5 (2023.findings-acl)
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| Challenge: | Recent years have seen several shifts in summarization research, including extractive models. |
| Approach: | They propose a pipeline method for applying GPT-3.5 to summarize user reviews . they propose three new metrics targeting faithfulness, factuality, and genericity . |
| Outcome: | The proposed methods perform well in opinion summarization, the authors show . they also show that standard evaluation metrics do not reflect this performance . |