Multilingual QA

QA: Question Answering

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7 papers in the last four weeks, up 133% on the four weeks before. 0.1% of all new papers.

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Where's Waldo? Query-language Preference under Cross-lingual Knowledge Disparities
Sep 30, 2026Dayeon Ki, Ruochen Zhang, Silviu Cucerzan +2Multilingual Language Model Evaluation Knowledge Conflicts in Language Models
University of Maryland · Microsoft
Cross-Lingual Legal QA for Vietnamese Labour Law: Retrieval, Translation, and Verifier-Guided Correction
Sep 23, 2026Nguyen Minh Chi, Mo El-Haj, Nguyen Ha Thanh +2LLM Answer Verification Legal Citation Verification
VinUniversity, Vietnam · Lancaster University, UK · Cardiff University, UK
VākQA: A Benchmark and Evaluation Study for Telugu Spoken Factoid Question Answering
Sep 17, 2026Bhavana Akkiraju, Ravi Sastry Kolluru, Sri Charan D +3Audio QA LLM-as-a-Judge
International Institute of Information Technology Hyderabad, India
SEAR: Segment-Evidence-Aware Routing for Weak-to-Strong Multilingual Speech MCQ
Sep 11, 2026Huy Hoang Le, Long-Bao Nguyen, Minh Tri DaoAudio-Language Model Evaluation Spoken Language Understanding
CAKE by VPBank, Vietnam
The Eloquence submission for Task 2 of the Interspeech 2026 MLC-SLM challenge
Sep 11, 2026Jordi Luque, Lorenzo Concina, Marco Matassoni +2Multilingual Language Model Evaluation Multilingual QA
Telefónica Innovación Digital, Scientific Group · Fondazione Bruno Kessler · Consiglio Nazionale delle Ricerche
IGT @ FinMMEval 2026 Task 2: Question-Type Prompting with Targeted Extraction for Multilingual Financial QA
Sep 8, 2026Yuwen ChiuFinancial QA Multilingual QA
Georgia Institute of Technology · Georgia Institute of Technology, North Ave NW, Atlanta, GA 30332
Perspectives on Cross-Lingual Consistency in LLMs for Medical Questions
Sep 7, 2026Minh Duc Bui, Mario Sanz-Guerrero, Abteen Ebrahimi +4Multilingual QA Cross-Lingual Consistency in Language Models
Johannes Gutenberg University Mainz, Germany · University of Colorado Boulder, USA · University of Marburg, Germany +1
A Systematic Evaluation of Cross-Lingual Consistency Enhancement Methods in Multilingual Language Models
Sep 3, 2026Jirui Qi, Mingyang Wang, Hinrich Schütze +2Multilingual Language Model Evaluation Multilingual QA
University of Groningen · LMU Munich · University of Amsterdam
XHotpotQA: A Benchmark for Cross-Lingual Knowledge Composition in Multi-Hop Question Answering
Aug 23, 2026Iman Barati, Arash Ghafouri, Behrouz Minaei-BidgoliMulti-Hop QA Cross-Lingual Reasoning in Language Models
School of Computer Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran
Better Decomposition, Free Aggregation: A Synthesizer-Folding Framework for Multilingual Multi-Hop Question Answering
Aug 13, 2026Yilin Wang, Yuchun Fan, Weidong Bao +5Multi-Hop QA Retrieval-Augmented Generation
School of Computer Science and Engineering, Northeastern University, Shenyang, China · Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, China
Measuring the Cross-Lingual Comprehension Gap: How the language of the evidence shapes what language models understand
Aug 6, 2026Rafael da Silva, Jeff EicherMultilingual Language Model Evaluation Multilingual QA
Eastern University
MultiGlobeQA: A Multilingual and Globally Diverse Benchmark for Geospatial Reasoning
Aug 4, 2026Martin Böckling, Elizaveta Nosova, Heiko Paulheim +1Multilingual Language Model Evaluation Spatial Reasoning Benchmarks
Data and Web Science Group, University of Mannheim, Germany
Language-Routed RAG and Direct Option Scoring for Multilingual Financial QA: DS@GT at FinMMEval
Jul 24, 2026Justice Ayela, Kabir SahniMultilingual Language Model Evaluation Retrieval-Augmented Generation
Georgia Institute of Technology, North Ave NW, Atlanta, GA 30332
When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMs
Jul 23, 2026Anna Mosolova, Djamé SeddahMultilingual Language Model Evaluation LLM Evaluation
INRIA Paris
Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering
Jul 22, 2026Zhuohan Xie, Xueqing Peng, Georgi Georgiev +18Multilingual Language Model Evaluation Financial QA
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates · The Fin AI, United States · FMI, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria +7
Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering
Jul 22, 2026Zhuohan Xie, Yuyang Dai, Rania Elbadry +18Multilingual Language Model Evaluation Multiple-Choice Question Answering
Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates · INSAIT, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria · University of Arizona, Tucson, United States +6
Efficiently Adapting Spoken Language Models for the Singaporean Context
Jul 11, 2026Ng Jia Sheng JasonSpoken Language Understanding Multi-Task Learning
Language AI R&D, xData Home Team Science & Technology Agency (HTX), Singapore
Estimating Uncertainty from Reasoning: A Large-Scale Study of Multi- and Crosslingual MCQA Performance in LLMs
Jul 7, 2026Andrea Bacciu, Andrea Alfarano, Saab Mansour +2Multilingual Language Model Evaluation Selective Prediction
Amazon · INSAIT, Sofia
MSQA: A Natively Sourced Multilingual and Multicultural SimpleQA Benchmark
Jul 1, 2026Xianru Chen, Yukai Huang, Mingxiang Chen +6Multilingual Language Model Evaluation LLM Evaluation
ByteDance Seed · Nanjing University · M-A-P
Causal Connections: Leveraging Multilingual Fine-Tuning for Financial QA@FinCausal 2026
Jun 25, 2026Akash Kumar Gautam, Serhii Hamotskyi, Christian HänigRelation Extraction LLM Fine-Tuning
Anhalt University of Applied Sciences
ChinaHeritaQA: A Culturally-Grounded Visual Question Answering Dataset for World Heritage Sites in China
Jun 8, 2026Yi Zhang, Bolei Ma, Yong Cao +3VLM Evaluation Visual Question Answering
1LMU Munich · 2FAU Erlangen-Nuremberg · 3Munich Center for Machine Learning +4
mmPISA-bench: Do LLMs Reason Equally Well Across 43 Languages?
Jun 5, 2026Yerzhan Sapenov, Jaromir SavelkaMultilingual Language Models Multilingual Language Model Evaluation
School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
Improving Cross-Lingual Factual Recall via Consistency-Driven Reinforcement Learning
Jun 4, 2026Jonathan von Rad, Louis Arts, George Burgess +6Multilingual Language Model Evaluation RL for Language Models
University College London, Centre for Artificial Intelligence
Simorgh at SemEval-2026 task 7: Region-Aware Hybrid Retrieval for Low-Resource Cultural Reasoning in Multilingual Question Answering
May 26, 2026Hadi Bayrami Asl Tekanlou, Mahdi Bakhtiyarzadeh, Jafar RazmaraRetrieval-Augmented Generation Cross-Lingual Reasoning in Language Models
University of Tabriz, Tabriz, Iran
Evaluating Commercial AI Chatbots as News Intermediaries
May 21, 2026Mirac Suzgun, Emily Shen, Federico Bianchi +5LLM Evaluation Question Answering
1Stanford University · 2Independent Researcher · 3Together AI.
A Comparative Study of Language Models for Khmer Retrieval-Augmented Question Answering
May 21, 2026Sereiwathna Ros, Phannet Pov, Ratanaktepi Chhor +3Retrieval-Augmented Generation Multilingual QA
Department of Computer Science, Chungbuk National University, Cheongju, South Korea · Department of Big Data, Chungbuk National University, Cheongju, South Korea · General Department of Information and Communication Technology, Ministry of Post and Telecommunications, Phnom Penh, Cambodia +2
FIND: Toward Multimodal Financial Reasoning and Question Answering for Indic Languages
May 13, 2026Sarmistha Das, Vaibhav Vishal, Syed Ibrahim Ahmad +2Financial Services Financial QA
Indian Institute of Technology Patna, India · Microsoft, India
Qwen Goes Brrr: Off-the-Shelf RAG for Ukrainian Multi-Domain Document Understanding
May 11, 2026Anton Bazdyrev, Ivan Bashtovyi, Ivan Havlytskyi +2Retrieval-Augmented Generation LLM Reranking
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Tatarstan Toponyms: A Bilingual Dataset and Hybrid RAG System for Geospatial Question Answering
May 7, 2026Mullosharaf K. ArabovQuestion Answering Geospatial Reasoning
Department of Data Analysis and Programming Technologies Institute of Computational Mathematics and Information Technologies Kazan (Volga Region) Federal University Kazan, Russia
CORAL: Adaptive Retrieval Loop for Culturally-Aligned Multilingual RAG
Apr 28, 2026Nayeon Lee, Jiwoo Song, Byeongcheol KangRetrieval-Augmented Generation Adaptive RAG
Naver · Samsung Research

Sep 30, 2026, cs.CLJ/K move · Enter open · S save

Where's Waldo? Query-language Preference under Cross-lingual Knowledge Disparities

Dayeon Ki, Ruochen Zhang, Silviu Cucerzan, Ryen W. White+1

University of Maryland · Microsoft

Multilingual Language Model Evaluation Knowledge Conflicts in Language Models Multilingual QA Cross-Lingual Consistency in Language Models

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Large Language Models increasingly serve as interfaces for knowledge-intensive information seeking tasks across languages by synthesizing multilingual evidence. Prior work has shown that they often exhibit query-language preference -- the tendency to favor sources written in the language of the query -- but has largely examined this behavior in settings where equivalent knowledge is available across languages. However, this bias becomes consequential when sources in different languages provide incomplete or inconsistent accounts of the same fact, since the information users receive then depends on the sources a model selects to use. To characterize query-language preference under such cross-lingual knowledge disparities, we introduce Waldo, a multilingual Question-Answering (QA) benchmark constructed from Wikipedia. Waldo contains 12K QA pairs targeting knowledge gaps, where a fact is available in one language but absent in another, and knowledge conflicts, where language editions provide conflicting versions of the same fact. Evaluating eight models across five languages, we find that when one language edition merely lacks the relevant fact, models generally use evidence from the other language regardless of the query language. Under conflicting accounts, however, model responses strongly align with the document in the query language, causing semantically equivalent queries to elicit different accounts depending on the user's language. Finally, we explore two different approaches that could mitigate this preference under knowledge conflicts: a mechanistic intervention that ablates attention heads associated with query-language preference, and LoRA-based training, which reduces the preference gap by up to 61.5%.

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