Papers with encoder-only pre-trained language models
Linguistic Cues for LLM-based Implicit Discourse Relation Classification (2026.findings-eacl)
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| Challenge: | Large language models (LLMs) have been successful in many NLP tasks, but they struggle to capture subtle lexical relations between arguments. |
| Approach: | They propose a strategy that enriches arguments with explicit lexical-level semantic cues before fine-tuning. |
| Outcome: | The proposed approach improves F1 scores in cross-domain scenarios by more than 10 points compared to baselines. |
An Exploration of Encoder-Decoder Approaches to Multi-Label Classification for Legal and Biomedical Text (2023.findings-acl)
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| Challenge: | Standard methods for multi-label text classification rely on encoder-only pre-trained models . encoder decoder models have proven more effective in other classification tasks . |
| Approach: | They compare four methods for multi-label classification based on encoder-only models . they use a pre-trained model for multilabel text classification . |
| Outcome: | The proposed methods outperform encoder-only methods on complex datasets and labeling schemes. |