KwaiYiiMath: Technical Report

Recent advancements in large language models (LLMs) have demonstrated remarkable abilities in handling a variety of natural language processing (NLP) downstream tasks, even on mathematical tasks requiring multi-step reasoning. In this report, we introduce the KwaiYiiMath which enhances the mathematical reasoning abilities of KwaiYiiBase1, by applying Supervised Fine-Tuning (SFT) and Reinforced Learning from Human Feedback (RLHF), including on both English and Chinese mathematical tasks. Meanwhile, we also constructed a small-scale Chinese primary school mathematics test set (named KMath), consisting of 188 examples to evaluate the correctness of the problem-solving process generated by the models. Empirical studies demonstrate that KwaiYiiMath can achieve state-of-the-art (SOTA) performance on GSM8k, CMath, and KMath compared with the similar size models, respectively.Comment: technical report. arXiv admin note: text overlap with arXiv:2306.16636 by other author

An in-memory computing architecture based on two-dimensional semiconductors for multiply-accumulate operations

In standard computing architectures, memory and logic circuits are separated, a feature that slows matrix operations vital to deep learning algorithms. Here, the authors present an alternate in-memory architecture and demonstrate a feasible approach for analog matrix multiplication

Cation-Exchange Approach to Tuning the Flexibility of a Metal–Organic Framework for Gated Adsorption

Achieving tailorable gated adsorption by tuning the dynamic behavior of a host porous material is of great interest because of its practical application in gas adsorption and separation. Here we devise a unique cation-exchange approach to tune the dynamic behavior of a flexible anionic framework, [Zn₂(bptc)­(datrz)]⁻ (denoted as MAC-6, where H₄bptc = [1,1′-biphenyl]-3,3′,5,5′-tetracarboxylic acid and Hdatrz = 3,5-diamine-1<i>H</i>-1,2,4-triazole), so as to realize the tailorable gated adsorption. The CO₂ adsorption amount at 273 K can be enhanced by exchanging the counterion of protonated dimethylamine (HDMA⁺) with tetraethylammonium (TEA⁺), tetrabutylammonium (TBA⁺), and tetramethylammonium (TMA⁺), where the adsorption behavior is transferred from nongated to gated adsorption. Interestingly, the <i>P</i>_go for gate-opening adsorption can be further tuned from 442 to 331 mmHg by simply adjusting the ratio of HDMA⁺ and TMA⁺. The origin of this unique tunable property, as revealed by X-ray diffraction experiments and structure models, is rooted at the cation-responsive characteristic of this flexible framework

Wafer-scale functional circuits based on two dimensional semiconductors with fabrication optimized by machine learning

10.1038/s41467-021-26230-xNature Communications121595