Papers with task-specific

2 papers
Walia-LLM: Enhancing Amharic-LLaMA by Integrating Task-Specific and Generative Datasets (2024.findings-emnlp)

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Challenge: Low-resource languages are left behind due to the unavailability of resources.
Approach: They propose to integrate task-specific and generative datasets to improve language model performance for Amharic by fine-tuning an Amharican instruction fine-to-tuned model.
Outcome: The proposed model shows promising results in different NLP tasks and compares translated instruction datasets with the original model.
Table-R1: Inference-Time Scaling for Table Reasoning Tasks (2025.emnlp-main)

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Challenge: In this study, we explore inference-time scaling on table reasoning tasks.
Approach: They propose a large-scale dataset of reasoning traces and a reinforcement learning with verifiable rewards approach to enable inference-time scaling on table reasoning tasks.
Outcome: The proposed model matches or exceeds GPT-4.1 and DeepSeek-R1 models on diverse table reasoning tasks.

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