| 1 |
Leveraging Unstructured Text Data for Federated Instruction Tuning of Large Language Models |
提出FedIT-U2S框架,利用非结构化文本数据进行联邦指令调优,扩展LLM应用场景。 |
large language model |
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| 2 |
Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language Model |
提出WikiOFGraph:利用大语言模型合成通用领域知识图谱到文本生成数据集,提升图文一致性。 |
large language model |
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| 3 |
Context-Aware Membership Inference Attacks against Pre-trained Large Language Models |
提出上下文感知成员推理攻击,针对预训练大语言模型的隐私风险 |
large language model |
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| 4 |
A Simplified Retriever to Improve Accuracy of Phenotype Normalizations by Large Language Models |
提出一种简化的检索器,通过大语言模型提升表型标准化的准确性 |
large language model |
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| 5 |
Recent Trends of Multimodal Affective Computing: A Survey from NLP Perspective |
综述:NLP视角下的多模态情感计算最新趋势研究 |
multimodal |
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| 6 |
Contextualization of ASR with LLM using phonetic retrieval-based augmentation |
提出基于音素检索增强的LLM语音识别上下文方法,提升命名实体识别准确率 |
large language model multimodal |
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| 7 |
Cross-Refine: Improving Natural Language Explanation Generation by Learning in Tandem |
提出Cross-Refine框架,通过生成器-评论家协同学习提升自然语言解释生成质量。 |
large language model |
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| 8 |
Understanding Knowledge Drift in LLMs through Misinformation |
研究LLM在虚假信息下的知识漂移现象,揭示其脆弱性并评估不确定性。 |
large language model |
✅ |
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| 9 |
Native vs Non-Native Language Prompting: A Comparative Analysis |
对比原生与非原生语言Prompt,探究其在阿拉伯语NLP任务中的性能差异 |
large language model |
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| 10 |
You Have Thirteen Hours in Which to Solve the Labyrinth: Enhancing AI Game Masters with Function Calling |
利用函数调用增强AI游戏大师,提升叙事质量与状态一致性 |
large language model |
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| 11 |
SimulBench: Evaluating Language Models with Creative Simulation Tasks |
SimulBench:提出创造性模拟任务评测基准,评估LLM在Linux终端和文本游戏等场景下的能力 |
large language model |
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| 12 |
MOSAIC: Multiple Observers Spotting AI Content |
提出MOSAIC,通过集成多个观测器LLM来更鲁棒地检测AI生成内容。 |
large language model |
✅ |
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| 13 |
Think Together and Work Better: Combining Humans' and LLMs' Think-Aloud Outcomes for Effective Text Evaluation |
提出InteractEval框架以提升文本评估效果 |
large language model |
✅ |
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