In recent years, there has been remarkable progress in leveraging Language Models (LMs),
encompassing Pre-trained Language Models (PLMs) and Large-scale Language Models …

Zero-shot Chain-of-Thought (CoT) prompting emerges as a simple and effective strategy for
enhancing the performance of large language models (LLMs) in real-world reasoning tasks …

The field of natural language processing (NLP) has witnessed significant progress in recent
years, with a notable focus on improving large language models'(LLM) performance through …

Prompt optimization emerges as an important technique for adapting Large Language
Models (LLMs) to specific tasks. Unfortunately, LLM proprietors often limit access to models' …

Large Language Models (LLMs) employing Chain-of-Thought (CoT) prompting have
broadened the scope for improving multi-step reasoning capabilities. We generally divide …

The reasoning abilities are one of the most enigmatic and captivating aspects of large
language models (LLMs). Numerous studies are dedicated to exploring and expanding the …

Recent advancements have highlighted that large language models (LLMs), when given a
small set of task-specific examples, demonstrate remarkable proficiency, a capability that …

Abstract The Emotional Support Conversation (ESC) task aims to alleviate emotional
distress in seekers and offer them an outlet for expressing their aggravation, garnering …

Since the introduction of Chain-of-Thought (CoT), leveraging Large Language Models
(LLMs) to solve complex reasoning problems has become possible. While an increasing …

Large language models (LLMs) have shown impressive performance in reasoning
benchmarks with the emergence of Chain-of-Thought (CoT), particularly in multi-choice …