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cs.CL2026
QAQ: Bidirectional Semantic Coherence for Selecting High-Quality Synthetic Code Instructions
Jiayin Lei, Ming Ma, Yunxi Duan +2
Synthetic data has become essential for training code generation models, yet it introduces significant noise and hallucinations that are difficult to detect with current metrics. E…
cs.CL2025
SimLens for Early Exit in Large Language Models: Eliciting Accurate Latent Predictions with One More Token
Ming Ma, Bowen Zheng, Zhongqiao Lin +1
Intermediate-layer predictions in large language models (LLMs) are informative but hard to decode accurately, especially at early layers. Existing lens-style methods typically rely…
cs.CL2024
Label Words as Local Task Vectors in In-Context Learning
Bowen Zheng, Ming Ma, Zhongqiao Lin +1
Large Language Models (LLMs) have demonstrated remarkable abilities, one of the most important being in-context learning (ICL). With ICL, LLMs can derive the underlying rule from a…