Papers with TAMA
TAMA: Target-Aware Multilingual Abuse Detection by Cascaded Conditional Multi-Task Learning (2026.acl-long)
Copied to clipboard
| Challenge: | Existing models for protecting public figures from online abuse ignore who is targeted and how. |
| Approach: | They propose a target-aware multi-task framework that conditions downstream predictions on upstream beliefs via three lightweight modules: Cross-Task Feature Fusion (CTF), Task-Adaptive Gating (TAG), and Label-Guided Span Detection (LGSD). |
| Outcome: | The proposed framework yields higher average F1 than single-task training and standard multi-task learning. |
Rethinking Table Instruction Tuning (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing studies have overlooked the impact of hyperparameters on table understanding abilities . authors show that smaller learning rates and fewer training instances can enhance table understanding while preserving general capabilities. |
| Approach: | They propose a hyperparameter-based instruction-tuned model for table-related tasks that improves out-of-domain table understanding ability and general capabilities. |
| Outcome: | The proposed model outperforms existing models on table-related tasks while maintaining strong out-of-domain generalization and general capabilities. |