Search Results for author:
Found 5 papers, 4 papers with code
Exploring Language Model's Code Generation Ability with Auxiliary Functions
However, our analysis also reveals the model's underutilized behavior to call the auxiliary function, suggesting the future direction to enhance their implementation by eliciting the auxiliary function call ability encoded in the models.
KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark
As language models are often deployed as chatbot assistants, it becomes a virtue for models to engage in conversations in a user's first language.
Toward Interpretable Semantic Textual Similarity via Optimal Transport-based Contrastive Sentence Learning
In the end, we propose CLRCMD, a contrastive learning framework that optimizes RCMD of sentence pairs, which enhances the quality of sentence similarity and their interpretation.
KLUE: Korean Language Understanding Evaluation
We introduce Korean Language Understanding Evaluation (KLUE) benchmark.
An Empirical Study of Tokenization Strategies for Various Korean NLP Tasks
Typically, tokenization is the very first step in most text processing works.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
