From the 1 of 9 linked papers with an AI index.
9 papers
EXPLORE: Exploration with Guided Search for Analog Topology Generation using Language Models
Guanglei Zhou, Chen-Chia Chang, Yikang Shen +5
The paper introduces EXPLORE, a framework that combines transformer-based language model decoding with simulator-guided Monte Carlo Tree Search to improve the generation of analog…
Finding the Minimal Parameter Budget for Implicit Reasoning: A Data Complexity Driven Scaling Law for Language Models
Xinyi Wang, Shawn Tan, Shenbo Xu +4
Reasoning is a core capability of language models (LMs), yet it remains unclear how much model capacity is necessary to support reasoning during pretraining. In this work, we study…
PaTH Attention: Position Encoding via Accumulating Householder Transformations
Songlin Yang, Yikang Shen, Kaiyue Wen +5
The attention mechanism is a core primitive in modern large language models (LLMs) and AI more broadly. Since attention by itself is permutation-invariant, position encoding is ess…
FlashFormer: Whole-Model Kernels for Efficient Low-Batch Inference
Aniruddha Nrusimha, William Brandon, Mayank Mishra +4
The size and compute characteristics of modern large language models have led to an increased interest in developing specialized kernels tailored for particular training and infere…
Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study
Shawn Tan, Songlin Yang, Aaron Courville +2
The self-attention mechanism traditionally relies on the softmax operator, necessitating positional embeddings like RoPE, or position biases to account for token order. But current…
API Pack: A Massive Multi-Programming Language Dataset for API Call Generation
Zhen Guo, Adriana Meza Soria, Wei Sun +2
We introduce API Pack, a massive multi-programming language dataset containing over one million instruction-API calls for improving the API call generation capabilities of large la…