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Found 7 papers, 0 papers with code
Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities
The results showed that the efficiency gained through vocabulary expansion had no negative impact on performance, except for the summarization task, and that the combined use of parallel corpora enhanced translation ability.
Building a Large Japanese Web Corpus for Large Language Models
Open Japanese large language models (LLMs) have been trained on the Japanese portions of corpora such as CC-100, mC4, and OSCAR.
Likelihood-based Mitigation of Evaluation Bias in Large Language Models
In this paper, we investigate the presence and impact of likelihood bias in LLM-based evaluators.
SAIE Framework: Support Alone Isn't Enough -- Advancing LLM Training with Adversarial Remarks
Large Language Models (LLMs) can justify or critique their predictions through discussions with other models or humans, thereby enriching their intrinsic understanding of instances.
Exploring Effectiveness of GPT-3 in Grammatical Error Correction: A Study on Performance and Controllability in Prompt-Based Methods
Large-scale pre-trained language models such as GPT-3 have shown remarkable performance across various natural language processing tasks.
Are Neighbors Enough? Multi-Head Neural n-gram can be Alternative to Self-attention
Impressive performance of Transformer has been attributed to self-attention, where dependencies between entire input in a sequence are considered at every position.
ExtraPhrase: Efficient Data Augmentation for Abstractive Summarization
Through experiments, we show that ExtraPhrase improves the performance of abstractive summarization tasks by more than 0. 50 points in ROUGE scores compared to the setting without data augmentation.
