Papers with auto-correction
Consistent Autoformalization for Constructing Mathematical Libraries (2024.emnlp-main)
Copied to clipboard
| Challenge: | Autoformalization is the task of automatically translating mathematical content written in natural language to a formal language expression. |
| Approach: | They propose to use three mechanisms to improve autoformalization quality . they propose to combine most-similar retrieval augmented generation, denoising steps and auto-correction with syntax error feedback to improve syntactic, terminological and semantic control. |
| Outcome: | The proposed mechanisms can deliver syntactically, terminologically and semantically more consistent results across different models. |
Can Active Label Correction Improve LLM-based Modular AI Systems? (2024.emnlp-main)
Copied to clipboard
| Challenge: | Large language models (LLMs) are powerful zero or few-shot learners and can generalize to a wide range of tasks without any model fine-tuning. |
| Approach: | They propose to use LLM annotations to train smaller task-specific improved models that can replace LLMs. |
| Outcome: | The proposed method can improve oracle performance with feedback on 17-24% fewer examples than the number of noisy examples in the dataset across three different NLP tasks. |