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20232026
most citedCoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction Tuning

1 citations · 1 across the 7 of their papers we have counts for

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cs.CL2025

CultureScope: A Dimensional Lens for Probing Cultural Understanding in LLMs

Jinghao Zhang, Sihang Jiang, Shiwei Guo +7

As large language models (LLMs) are increasingly deployed in diverse cultural environments, evaluating their cultural understanding capability has become essential for ensuring tru…

cs.CL2025

M-DaQ: Retrieving Samples with Multilingual Diversity and Quality for Instruction Fine-Tuning Datasets

Chunguang Zhao, Yilun Liu, Pufan Zeng +10

Multilingual instruction fine-tuning (IFT) empowers large language models to generalize across diverse linguistic and cultural contexts; however, high-quality, systematically curat…

cs.CL2025

ELSPR: Evaluator LLM Training Data Self-Purification on Non-Transitive Preferences via Tournament Graph Reconstruction

Yan Yu, Yilun Liu, Minggui He +9

Pairwise evaluation of large language models (LLMs) has become the dominant paradigm for benchmarking open-ended tasks, yet non-transitive preferences, where evaluators prefer A ov…

cs.CL2025

MIDB: Multilingual Instruction Data Booster for Enhancing Cultural Equality in Multilingual Instruction Synthesis

Yilun Liu, Chunguang Zhao, Xinhua Yang +9

Despite doubts on data quality, instruction synthesis has been widely applied into instruction tuning (IT) of LLMs as an economic and rapid alternative. Recent endeavors focus on i…

cs.CL2025

R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning

Minggui He, Yilun Liu, Shimin Tao +10

Despite recent breakthroughs in reasoning-enhanced large language models (LLMs) like DeepSeek-R1, incorporating inference-time reasoning into machine translation (MT), where human…