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Found 11 papers, 5 papers with code
Is Cognition and Action Consistent or Not: Investigating Large Language Model's Personality
In this study, we investigate the reliability of Large Language Models (LLMs) in professing human-like personality traits through responses to personality questionnaires.
Convergences and Divergences between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation
Large language models have demonstrated parallel and even superior translation performance compared to neural machine translation (NMT) systems.
Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach
The growing popularity of neural machine translation (NMT) and LLMs represented by ChatGPT underscores the need for a deeper understanding of their distinct characteristics and relationships.
MELA: Multilingual Evaluation of Linguistic Acceptability
Recent benchmarks for Large Language Models (LLMs) have mostly focused on application-driven tasks such as complex reasoning and code generation, and this has led to a scarcity in purely linguistic evaluation of LLMs.
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
In this work we systematically review the recent advancements in code processing with language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 800 related works.
Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach
It incorporates a framewise regularization term in CTC loss to emphasize individual supervision, and leverages the maximizing-a-posteriori of latent alignment to solve the inconsistency problem that arises in distillation between CTC-based models.
Revisiting Acceptability Judgements
We introduce CoLAC - Corpus of Linguistic Acceptability in Chinese, the first large-scale acceptability dataset for a non-Indo-European language.
Hedges in Bidirectional Translations of Publicity-Oriented Documents
Hedges are widely studied across registers and disciplines, yet research on the translation of hedges in political texts is extremely limited.
ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models
To address these challenges in English language teaching, we first present ArguGPT, a balanced corpus of 4, 038 argumentative essays generated by 7 GPT models in response to essay prompts from three sources: (1) in-class or homework exercises, (2) TOEFL and (3) GRE writing tasks.
Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer
Encoder-decoder models have made great progress on handwritten mathematical expression recognition recently.
NOSE Augment: Fast and Effective Data Augmentation Without Searching
The results establish our proposed method as a fast and competitive data augmentation strategy that can be used across various CV tasks.
