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Found 6 papers, 2 papers with code
Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators
Large Language Models (LLMs) have demonstrated promising capabilities as automatic evaluators in assessing the quality of generated natural language.
Unlocking Structure Measuring: Introducing PDD, an Automatic Metric for Positional Discourse Coherence
Recent large language models (LLMs) have shown remarkable performance in aligning generated text with user intentions across various tasks.
TOAD: Task-Oriented Automatic Dialogs with Diverse Response Styles
In light of recent advances in large language models (LLMs), the expectations for the next generation of virtual assistants include enhanced naturalness and adaptability across diverse usage scenarios.
Instruct-SCTG: Guiding Sequential Controlled Text Generation through Instructions
Instruction-tuned large language models have shown remarkable performance in aligning generated text with user intentions across various tasks.
Plug-and-Play Recipe Generation with Content Planning
Specifically, it optimizes the joint distribution of the natural language sequence and the global content plan in a plug-and-play manner.
Learning Functional Distributional Semantics with Visual Data
In this work, we propose a method to train a Functional Distributional Semantics model with grounded visual data.
