Measuring the relative impact of CTs is important for prioritizing responses and allocating
resources effectively, especially during crises. However, assessing the actual impact of CTs …

Well-designed prompts are crucial for enhancing Large language models'(LLMs) reasoning
capabilities while aligning their outputs with task requirements across diverse domains …

Recent multimodal large language models (MLLMs) have demonstrated significant potential
in open-ended conversation, generating more accurate and personalized responses …

LLM-as-a-Judge, which generates chain-of-thought (CoT) judgments, has become a widely
adopted auto-evaluation method. However, its reliability is compromised by the CoT …

Large Language Models have demonstrated remarkable capabilities in code generation, yet
they often struggle with complex programming tasks that require deep algorithmic …

Large Language Models (LLMs) require robust confidence estimation, particularly in critical
domains like healthcare and law where unreliable outputs can lead to significant …

Content analysis breaks down complex and unstructured texts into theory-informed
numerical categories. Particularly, in social science, this process usually relies on multiple …

While recent efforts have begun integrating large language models (LLMs) into foreign
language education (FLE), they often rely on traditional approaches to learning tasks without …

In a rapidly evolving knowledge landscape and the increasing adoption of large language
models, a need has emerged to keep these models continuously updated with current …

Code generation has attracted increasing attention with the rise of Large Language Models
(LLMs). Many studies have developed powerful code LLMs by synthesizing code-related …