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cs.CL2025
Evaluating LLMs Without Oracle Feedback: Agentic Annotation Evaluation Through Unsupervised Consistency Signals
Cheng Chen, Haiyan Yin, Ivor Tsang
Large Language Models (LLMs), when paired with prompt-based tasks, have significantly reduced data annotation costs and reliance on human annotators. However, evaluating the qualit…
cs.CL2025★ 1 cited
Can Post-Training Quantization Benefit from an Additional QLoRA Integration?
Xiliang Zhu, Elena Khasanova, Cheng Chen
Large language models (LLMs) have transformed natural language processing but pose significant challenges for real-world deployment. These models necessitate considerable computing…