In this study, we reveal an in-context learning (ICL) capability of multilingual large language models (LLMs): by translating the input to several languages, we provide Parallel Input in Multiple Languages (PiM) to LLMs, which significantly enhances their comprehension abilities. To test this capability, we design extensive experiments encompassing 8 typical datasets, 7 languages and 8 state-of-the-art multilingual LLMs. Experimental results show that (1) incorporating more languages help PiM surpass the conventional ICL further; (2) even combining with the translations that are inferior to baseline performance can also help. Moreover, by examining the activated neurons in LLMs, we discover a counterintuitive but interesting phenomenon. Contrary to the common thought that PiM would activate more neurons than monolingual input to leverage knowledge learned from diverse languages, PiM actually inhibits neurons and promotes more precise neuron activation especially when more languages are added. This phenomenon aligns with the neuroscience insight about synaptic pruning, which removes less used neural connections, strengthens remainders, and then enhances brain intelligence.
A Recipe of Parallel Corpora Exploitation for Multilingual Large Language Models
LMU Munich（慕尼黑大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）；Instituto Superior Técnico, Universidade de Lisboa（里斯本大学高等技术学院）；Instituto de Telecomunicações（电信研究所）；Unbabel（昂巴贝尔公司）
MITRA: A Large-Scale Parallel Corpus and Multilingual Pretrained Language Model for Machine Translation and Semantic Retrieval for Pāli, Sanskrit, Buddhist Chinese, and Tibetan
Center for Integrated Japanese Studies, Tohoku University（东京东京大学综合日语研究机构）；University of California, Berkeley（加州大学伯克利分校）；Berkeley Artificial Intelligence Research (BAIR)（伯克利人工智能研究（BAIR））
From Unaligned to Aligned: Scaling Multilingual LLMs with Multi-Way Parallel Corpora
Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）；Technical University of Munich（慕尼黑技术大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）；Minzu University of China（民族大学）；Institute for AI, Tsinghua University（清华大学人工智能研究院）
MathMist: A Parallel Multilingual Benchmark Dataset for Mathematical Problem Solving and Reasoning
BRAC University（布拉克大学）；United International University（国际联合大学）；Qatar Computing Research Institute（卡塔尔计算研究所）；Center for Computational & Data Sciences, Independent University, Bangladesh（计算与数据科学中心，独立大学，孟加拉国）；Amazon GenAI（亚马逊生成人工智能）；University of Virginia（弗吉尼亚大学）
The Role of Mixed-Language Documents for Multilingual Large Language Model Pretraining
University College London（伦敦大学学院）；Nanyang Technological University（南洋理工大学）；University of Waterloo（滑铁卢大学）；NVIDIA（英伟达）；National Institute of Informatics（信息研究院）
Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation
Technische Universität Berlin（柏林工业大学）；German Research Center for Artificial Intelligence (DFKI)（德国人工智能研究中心（DFKI））；University of Marburg（马尔堡大学）；LMU Munich（慕尼黑大学）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心（MCML））；BIFOLD – Berlin Institute for the Foundations of Learning and Data（柏林学习与数据基础研究所（BIFOLD））
XToM: Exploring the Multilingual Theory of Mind for Large Language Models
HKUST, Hong Kong（香港理工大学）；NVIDIA AI Technology Center (NVAITC), USA（NVIDIA AI技术中心（NVAITC））；Shanghai Jiao Tong University, China（上海交通大学）；Technische Universtität Darmstadt, Germany（德累斯顿技术大学）；LMU Munich, Germany（慕尼黑大学）；Munich Center for Machine Learning, Germany（慕尼黑机器学习中心）
Qwenfant: Train Big Character-level BabyLMs on Concise Parallel Text
School of Computation, Information and Technology, TU Munich（慕尼黑工业大学计算、信息与技术学院）；Munich Center for Machine Learning（慕尼黑机器学习中心）；Munich Data Science Institute（慕尼黑数据科学研究所）
Separating Grains from the Chaff: Using Data Filtering to Improve Multilingual Translation for Low-Resourced African Languages
TUM（慕尼黑工业大学）；Mila - Quebec AI Institute（米拉-魁北克人工智能研究所）；University of Cape Town（开普敦大学）；African Institute for Mathematical Sciences（非洲数学科学研究所）；Luleå University of Technology（吕勒奥理工大学）；LIAAD-INESC TEC（LIAAD-INESC科技与工程研究所）；Uppsala University（乌普萨拉大学）；Ford Motor Company（福特汽车公司）；University of Chinese Academy of Sciences（中国科学院大学）；Ahmadu Bello University（艾哈迈德·贝罗大学）；University of the Witwatersrand（威特沃特斯兰德大学）；Saarland University（萨尔大学）
Multilingual Brain Surgeon: Large Language Models Can be Compressed Leaving No Language Behind
X-LANCE Lab, Department of Computer Science and Engineering MoE Key Lab of Artificial Intelligence, SJTU AI Institute Shanghai Jiao Tong University, Shanghai, China（X-LANCE实验室，计算机科学与工程系，MoE人工智能关键实验室，上海交通大学人工智能研究院，上海，中国）；Suzhou Laboratory, Suzhou, China（苏州实验室，苏州，中国）
Mind the Gap: Exposing LLM Translation Blind Spots Using the AlphaMWE Multilingual Parallel Corpus
Leiden University（莱顿大学）；Leiden University Medical Centre（莱顿大学医学中心）；Institute of Computer Science PAS, Warsaw（波兰科学院计算机科学研究所）；University of Ljubljana（卢布尔雅那大学）；University of Granada（格拉纳达大学）；Technical University of Munich（慕尼黑工业大学）；Heinrich Heine University Düsseldorf（杜塞尔多夫海因里希·海涅大学）；Google DeepMind（谷歌DeepMind）
Multilingual and Explainable Text Detoxification with Parallel Corpora
Technical University of Munich（慕尼黑工业大学）；Universidade de Santiago de Compostela（圣地亚哥-德孔波斯特拉大学）；Shenkar College（申卡尔学院）；University of Hamburg（汉堡大学）；Bahir Dar University（巴达尔大学）；IIT Kharagpur（印度理工学院克勒格布尔分校）；Skoltech（斯科尔科沃科技学院）；AIRI（人工智能研究所）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；University of Sharjah（沙迦大学）
Facts are Harder Than Opinions -- A Multilingual, Comparative Analysis of LLM-Based Fact-Checking Reliability
GESIS – Leibniz Institute for the Social Sciences（GESIS社会科学院研究所）；RWTH Aachen University（亚琛RWTH大学）；University of Graz（格拉茨大学）；Complexity Science Hub（复杂性科学中心）
CodePivot: Bootstrapping Multilingual Transpilation in LLMs via Reinforcement Learning without Parallel Corpora
The Hong Kong University of Science and Technology（香港科学与技术大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））；Monash University（莫纳什大学）；The Chinese University of Hong Kong（香港中文大学）
ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus
Center for Information and Language Processing (CIS), LMU Munich（慕尼黑大学信息与语言处理中心（CIS））；Research Center Deutscher Sprachatlas, Philipps University Marburg（马尔堡菲利普大学德国语言地图集研究中心）
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation
School of Mathematical and Computational Sciences, Massey University（马歇尔大学数学与计算科学学院）；Mila – Quebec AI Institutes（魁北克人工智能研究院）；Computer Science, Ontario Technology University and University of Toronto（安大略技术大学与多伦多大学计算机科学系）
