67 citations · 80 across the 8 of their papers we have counts for
17 papers · 1 filter
Competition-Level Problems are Effective LLM Evaluators
Yiming Huang, Zhenghao Lin, Xiao Liu +8
Large language models (LLMs) have demonstrated impressive reasoning capabilities, yet there is ongoing debate about these abilities and the potential data contamination problem rec…
EIPE-text: Evaluation-Guided Iterative Plan Extraction for Long-Form Narrative Text Generation
Wang You, Wenshan Wu, Yaobo Liang +8
Plan-and-Write is a common hierarchical approach in long-form narrative text generation, which first creates a plan to guide the narrative writing. Following this approach, several…
GameEval: Evaluating LLMs on Conversational Games
Dan Qiao, Chenfei Wu, Yaobo Liang +2
The rapid advancements in large language models (LLMs) have presented challenges in evaluating those models. Existing evaluation methods are either reference-based or preference ba…
Analyzing and Reducing the Performance Gap in Cross-Lingual Transfer with Fine-tuning Slow and Fast
Yiduo Guo, Yaobo Liang, Dongyan Zhao +2
Existing research has shown that a multilingual pre-trained language model fine-tuned with one (source) language also performs well on downstream tasks for non-source languages, ev…
Machine-Created Universal Language for Cross-lingual Transfer
Yaobo Liang, Quanzhi Zhu, Junhe Zhao +1
There are two primary approaches to addressing cross-lingual transfer: multilingual pre-training, which implicitly aligns the hidden representations of various languages, and trans…
Learning to Plan with Natural Language
Yiduo Guo, Yaobo Liang, Chenfei Wu +3
Large Language Models (LLMs) have shown remarkable performance in various basic natural language tasks. For completing the complex task, we still need a plan for the task to guide…