Large Language Model
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AbstractAI researchers have posited Dungeons and Dragons (D&D) as a challenge problem to test systems on various language-related capabilities. In this paper, we frame D&D specifically as a dialogue system …...
Analyzing ChatGPT’s Mathematical Deficiencies: Insights and Contributions
In this study, we assess ChatGPT, OpenAI’s latest conversational chatbot and large lan- guage model (LLM), on its performance in elementary-grade arithmetic and logic prob- lems. Despite its impressive coherence …...
Code4Struct: Code Generation for Few-Shot Event Structure Prediction
AbstractLarge Language Model (LLM) trained on a mixture of text and code has demonstrated impressive capability in translating natural language (NL) into structured code. We observe that semantic structures can …...
Evaluating Interfaced LLM Bias
In this research, we comprehensively ana- lyze the potential biases inherent in Large Language Model, utilizing meticulously cu- rated input data to ascertain the extent to which such data sway …...
Introducing Semantics into Speech Encoders
AbstractRecent studies find existing self-supervised speech encoders contain primarily acoustic rather than semantic information. As a result, pipelined supervised automatic speech recognition (ASR) to large language model (LLM) systems achieve …...
Large Language Models Meet NL2Code: A Survey
AbstractThe task of generating code from a natural language description, or NL2Code, is considered a pressing and significant challenge in code intelligence. Thanks to the rapid development of pre-training techniques, …...
RARR: Researching and Revising What Language Models Say, Using Language Models
AbstractLanguage models (LMs) now excel at many tasks such as question answering, reasoning, and dialog. However, they sometimes generate unsupported or misleading content. A user cannot easily determine whether their …...