| 1 |
ProgCo: Program Helps Self-Correction of Large Language Models |
ProgCo:利用程序辅助大语言模型进行自我纠错,提升复杂推理能力 |
large language model instruction following |
✅ |
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| 2 |
Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models |
构建Singlish理解桥梁:发布数据集与多模态模型SingAudioLLM |
large language model multimodal |
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| 3 |
Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs |
SafeNudge:一种可调安全-性能权衡的LLM实时安全防护方法 |
large language model |
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| 4 |
Cross-model Transferability among Large Language Models on the Platonic Representations of Concepts |
提出线性变换方法,实现大语言模型间概念表示的跨模型迁移与行为控制。 |
large language model |
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| 5 |
Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case |
探索大语言模型辅助精神健康诊断评估:以抑郁症和焦虑症为例 |
large language model |
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| 6 |
Does a Large Language Model Really Speak in Human-Like Language? |
提出统计假设检验框架以比较LLM与人类文本的相似性 |
large language model |
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| 7 |
Large Language Model-Enhanced Symbolic Reasoning for Knowledge Base Completion |
提出LLM增强的符号推理框架,用于提升知识库补全的灵活性和可靠性 |
large language model |
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| 8 |
Dynamic Attention-Guided Context Decoding for Mitigating Context Faithfulness Hallucinations in Large Language Models |
提出动态注意力引导的上下文解码DAGCD,缓解大语言模型中的上下文忠实性幻觉问题 |
large language model |
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| 9 |
Risks of Cultural Erasure in Large Language Models |
评估大型语言模型中文化抹除风险,关注遗漏与简化两种形式 |
large language model |
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| 10 |
MDSF: Context-Aware Multi-Dimensional Data Storytelling Framework based on Large language Model |
MDSF:基于大语言模型的上下文感知多维数据故事讲述框架 |
large language model |
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| 11 |
Exploring Information Processing in Large Language Models: Insights from Information Bottleneck Theory |
基于信息瓶颈理论探索大语言模型的信息处理机制,并提出IC-ICL和TS-FT方法。 |
large language model |
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| 12 |
Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection |
提出基于语义图增强不确定性建模的幻觉检测方法 |
large language model |
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| 13 |
OmniChat: Enhancing Spoken Dialogue Systems with Scalable Synthetic Data for Diverse Scenarios |
OmniChat:利用可扩展的合成数据增强口语对话系统,覆盖多样化场景 |
large language model |
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| 14 |
Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking |
提出HaluSearch框架,通过快慢双重思维过程缓解大语言模型的幻觉问题 |
large language model |
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| 15 |
CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings |
CodeElo:提出基于Elo等级分的LLM代码生成能力竞赛级评测基准 |
large language model |
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| 16 |
Self-Refinement Strategies for LLM-based Product Attribute Value Extraction |
研究表明,基于LLM的自精炼策略在产品属性值抽取任务中未能有效提升性能。 |
large language model |
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| 17 |
BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference |
BlockDialect:面向节能LLM推理的块状细粒度混合格式量化 |
large language model |
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| 18 |
Dynamic Scaling of Unit Tests for Code Reward Modeling |
提出CodeRM-8B,通过动态调整单元测试规模提升代码奖励建模性能 |
large language model |
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| 19 |
FED: Fast and Efficient Dataset Deduplication Framework with GPU Acceleration |
FED:基于GPU加速的高效数据集去重框架,提升LLM训练效率 |
large language model |
✅ |
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| 20 |
ValuesRAG: Enhancing Cultural Alignment Through Retrieval-Augmented Contextual Learning |
提出ValuesRAG,通过检索增强上下文学习提升LLM的跨文化价值观对齐能力 |
large language model |
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| 21 |
KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model |
KaLM-Embedding:通过高质量训练数据提升通用多语言嵌入模型性能 |
large language model |
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