4 papers
Mitigating Conversational Inertia in Multi-Turn Agents
Yang Wan, Zheng Cao, Zhenhao Zhang +4
Large language models excel as few-shot learners when provided with appropriate demonstrations, yet this strength becomes problematic in multiturn agent scenarios, where LLMs erron…
Effective Learning for Small Reasoning Models: An Empirical Study on 0.5B Reasoning LLMs
Xialie Zhuang, Peixian Ma, Zhikai Jia +2
The ongoing evolution of language models has led to the development of large-scale architectures that demonstrate exceptional performance across a wide range of tasks. However, the…
Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More
Xialie Zhuang, Zhikai Jia, Jianjin Li +4
Large Language Models (LLMs) are discovered to suffer from accurately retrieving key information. To address this, we propose Mask-Enhanced Autoregressive Prediction (MEAP), a simp…
Exploring Intrinsic Language-specific Subspaces in Fine-tuning Multilingual Neural Machine Translation
Zhe Cao, Zhi Qu, Hidetaka Kamigaito +1
Multilingual neural machine translation models support fine-tuning hundreds of languages simultaneously. However, fine-tuning on full parameters solely is inefficient potentially l…