2 research outputs found
Evaluating the Capability of Large-scale Language Models on Chinese Grammatical Error Correction Task
Large-scale language models (LLMs) has shown remarkable capability in various
of Natural Language Processing (NLP) tasks and attracted lots of attention
recently. However, some studies indicated that large language models fail to
achieve promising result beyond the state-of-the-art models in English
grammatical error correction (GEC) tasks. In this report, we aim to explore the
how large language models perform on Chinese grammatical error correction tasks
and provide guidance for future work. We conduct experiments with 3 different
LLMs of different model scale on 4 Chinese GEC dataset. Our experimental
results indicate that the performances of LLMs on automatic evaluation metrics
falls short of the previous sota models because of the problem of
over-correction. Furthermore, we also discover notable variations in the
performance of LLMs when evaluated on different data distributions. Our
findings demonstrates that further investigation is required for the
application of LLMs on Chinese GEC task
A Bubble-Assisted Approach for Patterning Nanoscale Molecular Aggregates
We demonstrate a new approach to pattern functional organic molecules with a template of foams, and achieve a resolution of sub 100 nm. The bubble-assisted assembly (BAA) process is consisted of two periods, including bubble evolution and molecular assembly, which are dominated by the Laplace pressure and molecular interactions, respectively. Using TPPS (meso-tetra(4-sulfonatophenyl) porphyrin), we systematically investigate the patterns and assembly behaviour in the bubble system with a series of characterizations, which show good uniformity in nanoscale resolution. Theoretical simulations reveal that TPPS's J-aggregates contribute to the ordered construction of molecular patterns. Finally, we propose an empirical rule for molecular patterning approach, that the surfactant and functional molecules should have the same type of charge in a two-component system. This approach exhibits promising feasibility to assemble molecular patterns at nanoscale resolution for micro/nano functional devices