Papers by Zhihong Jin
CycleOIE: A Low-Resource Training Framework For Open Information Extraction (2025.coling-main)
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Zhihong Jin, Chunhong Zhang, Zheng Hu, Jibin Yu, Ruiqi Ma, Qingyun Chen, Xiaohao Liao, Yanxing Zhang
| Challenge: | Open Information Extraction (OpenIE) models rely heavily on large amounts of annotated data. |
| Approach: | They propose a training framework that maximizes data efficiency through a cycle-consistency mechanism. |
| Outcome: | The proposed approach improves the quality of training data by curating low-quality datasets annotated by a large language model. |
LOOK-M: Look-Once Optimization in KV Cache for Efficient Multimodal Long-Context Inference (2024.findings-emnlp)
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| Challenge: | Long-context Multimodal Large Language Models (MLLMs) require substantial computational resources for inference . the growth of their multimodal Key-Value (KV) cache challenges memory and time efficiency. |
| Approach: | They propose a fine-tuning-free approach that efficiently reduces the multimodal KV cache size while maintaining performance comparable to a full cache. |
| Outcome: | The proposed method reduces the multimodal KV cache size while maintaining performance comparable to a full cache. |
Enhancing Code Generation Performance of Smaller Models by Distilling the Reasoning Ability of LLMs (2024.lrec-main)
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| Challenge: | Large Language Models (LLMs) have made significant advances in code generation through the ‘Chain-of-Thought’ prompting technique. |
| Approach: | They propose a framework which aims to transfer LLMs’ reasoning capabilities to smaller models through distillation. |
| Outcome: | The proposed framework improves the smaller model's code generation performance by over 130% on the APPS benchmark. |