8 papers
AutoVerus: Automated Proof Generation for Rust Code
Chenyuan Yang, Xuheng Li, Md Rakib Hossain Misu +10
Generative AI has shown its values for many software engineering tasks. Still in its infancy, large language model (LLM)-based proof generation lags behind LLM-based code generatio…
WaferLLM: Large Language Model Inference at Wafer Scale
Congjie He, Yeqi Huang, Pei Mu +5
Emerging AI accelerators increasingly adopt wafer-scale manufacturing technologies, integrating hundreds of thousands of AI cores in a mesh architecture with large distributed on-c…
SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs
Yizhao Gao, Zhichen Zeng, Dayou Du +8
Attention is the cornerstone of modern Large Language Models (LLMs). Yet its quadratic complexity hinders efficiency and scalability, especially for long-context processing. A prom…
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Xinyu Guan, Li Lyna Zhang, Yifei Liu +5
We present rStar-Math to demonstrate that small language models (SLMs) can rival or even surpass the math reasoning capability of OpenAI o1, without distillation from superior mode…
RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval
Di Liu, Meng Chen, Baotong Lu +11
Transformer-based Large Language Models (LLMs) have become increasingly important. However, due to the quadratic time complexity of attention computation, scaling LLMs to longer co…
Neuro-Symbolic Data Generation for Math Reasoning
Zenan Li, Zhi Zhou, Yuan Yao +5
A critical question about Large Language Models (LLMs) is whether their apparent deficiency in mathematical reasoning is inherent, or merely a result of insufficient exposure to hi…