3 papers
cs.CL2026
KCS: Diversify Multi-hop Question Generation with Knowledge Composition Sampling
Yangfan Wang, Jie Liu, Chen Tang +2
Multi-hop question answering faces substantial challenges due to data sparsity, which increases the likelihood of language models learning spurious patterns. To address this issue,…
cs.CL2026
KA2L: A Knowledge-Aware Active Learning Framework for LLMs
Haoxuan Yin, Bojian Liu, Chen Tang +3
Fine-tuning large language models (LLMs) with high-quality knowledge has been shown to enhance their performance effectively. However, there is a paucity of research on the depth o…
cs.CL2025
AgriEval: A Comprehensive Chinese Agricultural Benchmark for Large Language Models
Lian Yan, Haotian Wang, Chen Tang +5
In the agricultural domain, the deployment of large language models (LLMs) is hindered by the lack of training data and evaluation benchmarks. To mitigate this issue, we propose Ag…