3 papers
cs.CL2025
StructFlowBench: A Structured Flow Benchmark for Multi-turn Instruction Following
Jinnan Li, Jinzhe Li, Yue Wang +2
Multi-turn instruction following capability constitutes a core competency of large language models (LLMs) in real-world applications. Existing evaluation benchmarks predominantly f…
cs.CL2024
Language Models can Evaluate Themselves via Probability Discrepancy
Tingyu Xia, Bowen Yu, Yuan Wu +2
In this paper, we initiate our discussion by demonstrating how Large Language Models (LLMs), when tasked with responding to queries, display a more even probability distribution in…
cs.CL2024
NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli
Xu Wang, Cheng Li, Yi Chang +2
Large Language Models (LLMs) have become integral to a wide spectrum of applications, ranging from traditional computing tasks to advanced artificial intelligence (AI) applications…