Papers with modular adapters
Multi-Task Pre-Finetuning of Lightweight Transformer Encoders for Text Classification and NER (2025.emnlp-industry)
Copied to clipboard
| Challenge: | nave multitask pre-finetuning introduces conflicting optimization signals that degrade overall performance. |
| Approach: | They propose a framework that enables a single shared encoder backbone with modular adapters. |
| Outcome: | The proposed framework achieves comparable performance to individual pre-finetuning while meeting practical deployment constraint. |
Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey (2025.findings-emnlp)
Copied to clipboard
| Challenge: | specialized LLMs are often limited in domain-specific applications that require specialized knowledge. |
| Approach: | They provide a comprehensive overview of four key methods to enhance large language models by integrating domain-specific knowledge. |
| Outcome: | The proposed methods are categorized into four key approaches: dynamic knowledge injection, static knowledge embedding, modular adapters, and prompt optimization. |