5 papers
Predicting Mergeability of Parameter-Efficient Fine-Tuning Updates
Lin Tang, Wei Zhang, Jing Li +3
Low-rank adaptation (LoRA) makes it cheap to train many domain- and task-specific language model adapters, but whether two adapters can be merged is usually discovered only after b…
SuCo: Sufficiency-guided Continuous Adaptive Reasoning
Jiahao Wang, Bingyu Liang, Chenhao Hu +5
Despite remarkable performance on complex tasks, Large Reasoning Models (LRMs) often generate excessively long Chain-of-Thoughts (CoT), inflating computational costs even for simpl…
Bridging Functional Correctness and Runtime Efficiency Gaps in LLM-Based Code Translation
Longhui Zhang, Jiahao Wang, Chenhao Hu +3
While large language models (LLMs) have greatly advanced the functional correctness of automated code translation systems, the runtime efficiency of translated programs has receive…
System Report for CCL25-Eval Task 10: SRAG-MAV for Fine-Grained Chinese Hate Speech Recognition
Jiahao Wang, Ramen Liu, Longhui Zhang +1
This paper presents our system for CCL25-Eval Task 10, addressing Fine-Grained Chinese Hate Speech Recognition (FGCHSR). We propose a novel SRAG-MAV framework that synergistically…
Function-to-Style Guidance of LLMs for Code Translation
Longhui Zhang, Bin Wang, Jiahao Wang +7
Large language models (LLMs) have made significant strides in code translation tasks. However, ensuring both the correctness and readability of translated code remains a challenge,…