| 1 |
Numeracy in Large Language Models: Fundamental Limitations and Paths to Improvement |
提出数值基础框架以解决大语言模型的数值理解问题 |
large language model foundation model |
|
|
| 2 |
DMDIntel: Interpreting Large Language Models via Dynamic Mode Decomposition |
提出DMDIntel以提升大语言模型预测的可解释性 |
large language model |
|
|
| 3 |
Generative Universal Multimodal Retrieval with Dual-role Identifiers |
提出DrIG框架以解决多模态检索中的效率与准确性问题 |
multimodal |
|
|
| 4 |
SynAct: A Reasoning-Acting Large Language Model Agent for Adaptive Synthesis Optimization |
提出SynAct以解决逻辑综合优化中的适应性问题 |
large language model |
|
|
| 5 |
Keep, Customize, or Exit: Default Design and Token Pricing in LLM Reasoning Services |
提出基于Stackelberg博弈的LLM服务定价与默认分配策略 |
large language model |
|
|
| 6 |
OmniScientist: An Omni-Modal Omni-Discipline AI Scientist |
提出OmniScientist以解决科学发现中的证据获取问题 |
foundation model |
|
|
| 7 |
CAPRI: Contract-Aware Proof Repair for Isabelle |
提出CAPRI以解决Isabelle证明中的合同意识问题 |
large language model |
|
|
| 8 |
RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level |
提出RAIL以自动评估人工智能技术的成熟度 |
large language model |
|
|
| 9 |
vToken: Token-Level Virtualization for Reclaimable KV Caches |
提出vToken以解决KV缓存的内存回收问题 |
large language model |
|
|
| 10 |
TsuGO: Probing Search Efficiency in LLM Reasoning via Go Life-and-Death Problems |
提出TsuGO以评估LLM推理中的搜索效率问题 |
chain-of-thought |
|
|
| 11 |
SPADE: Speculative Decoding for Precise and Low Cost Distributed Edge Cloud Inference |
提出SPADE框架以解决边缘云推理的高成本与低精度问题 |
large language model |
|
|
| 12 |
Beyond Handcrafted Security: Towards Self-Evolving Defense for LLM Agents |
提出HARD框架以实现自我演化的LLM代理防御机制 |
large language model |
|
|
| 13 |
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference |
提出E2-Explainer以解决LLM多智能体系统通信拓扑可解释性问题 |
large language model |
|
|
| 14 |
Memorization Diagnostics for Code LLMs Should be Scale-Aware |
提出规模感知的记忆诊断方法以解决代码LLM的理解问题 |
large language model |
|
|
| 15 |
PROVE-RT: Generating Mechanized Theorem Prover Scripts for Real-Time Systems using LLMs |
提出PROVE-RT以解决实时系统的可调度性分析问题 |
large language model |
|
|
| 16 |
Tracing Provenance and Detecting Tampering with Complementary LLM Watermarks |
提出一种新型水印技术以解决LLM文本溯源与篡改检测问题 |
large language model |
|
|
| 17 |
Privacy-Preserving RAG by Concealing Sensitive Information from External LLMs |
提出SEAG框架以保护RAG中的敏感信息 |
large language model |
|
|
| 18 |
On the Expressive Power of Transformers |
通过电路复杂性分析变换器的表达能力 |
large language model |
|
|
| 19 |
SynAct: A Reasoning-Acting Large Language Model Agent for Adaptive Synthesis Optimization |
提出SynAct以解决逻辑综合优化中的适应性问题 |
large language model |
|
|
| 20 |
Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement |
提出基于仿真的LLM多智能体框架以优化模拟电路布局 |
large language model |
|
|
| 21 |
Fine-Tuning Qwen3-27B for C-to-Rust Code Translation: A Three-Stage Curriculum of Pretraining, Debugging-Aware SFT, and Task-Specific SFT |
提出三阶段微调方案以解决C到Rust代码翻译问题 |
large language model |
|
|
| 22 |
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference |
提出E2-Explainer以解决LLM多智能体系统通信拓扑可解释性问题 |
large language model |
|
|