--- title: "Fengran Mo — author profile and papers — Elamur Research" description: "Fengran Mo, University of Notre Dame: 8 papers on Elamur Research (2026), h-index 14 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/fengran-mo/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/fengran-mo/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Fengran Mo # Fengran Mo Fengran Mo has 8 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/), [Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/); often with [Meng Jiang](https://md.research.elamur.ai/free/en/authors/meng-jiang/), [Zhaoxuan Tan](https://md.research.elamur.ai/free/en/authors/zhaoxuan-tan/), [Jian-Yun Nie](https://md.research.elamur.ai/free/en/authors/jian-yun-nie/). 8 papers in our library · 2026 [OpenAlex](https://openalex.org/A5048033573) · [ORCID](https://orcid.org/0000-0002-0838-6994) · [Wikidata](https://www.wikidata.org/wiki/Q130855841) · [**h-index 14**](https://openalex.org/authors/A5048033573) · [106 works](https://openalex.org/works?filter=author.id:A5048033573) · [514 citations](https://openalex.org/works?filter=author.id:A5048033573&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 8 works in our library](https://md.research.elamur.ai/free/en/authors/fengran-mo/#papers) · [🔗 Cited 57 times in our library](https://md.research.elamur.ai/free/en/authors/fengran-mo/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #9411](https://md.research.elamur.ai/free/en/paper-stars/page/95/#star-9411) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Fengran+Mo) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Fengran+Mo) · [dblp](https://dblp.org/search?q=Fengran+Mo) · [ACL Anthology](https://aclanthology.org/search/?q=Fengran+Mo) ## Affiliations [🎓**Université de Montréal** Montreal · Canada 2022–2026 · 101 papersEducation 2022–2026 · PhD, Department of Computer Science and Operations ResearchEmployment 2022–2026 · PhD Student, DIRO*current*](https://md.research.elamur.ai/free/en/universities/universite-de-montreal/) · [🎓**Beijing Jiaotong University** Beijing · China 2025–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/beijing-jiaotong-university/) · [🎓**University of Notre Dame** Notre Dame · United States 2025–2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-notre-dame/) · [🎓**Rochester Institute of Technology** Rochester · United States 2026 · 2 papersEmployment since 2026 · Department of Computer Science*current*](https://md.research.elamur.ai/free/en/universities/rochester-institute-of-technology/) · [🎓**Tsinghua University** Beijing · China 2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) · [🏢**Salesforce** San Francisco · United States 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/salesforce/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 8 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 8 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Information Systems · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Social Sciences · 2 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [General Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/general-social-sciences/) · [Literature and Literary Theory · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/literature-and-literary-theory/) 🧭 Topics 8 Research subjects and languages the work is about.[Language models & pretraining · 4 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Information retrieval & search · 2 works](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Multilingual & cross-lingual NLP · 2 works](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Dialogue systems · 2 works](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Bias, fairness & safety · 2 works](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 8 papers](https://md.research.elamur.ai/free/en/authors/fengran-mo/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/qi-2026-language-coupled-reinforcement-learning-multilingual/)** *(2026 · 5 citations)* The paper addresses two problems in multilingual retrieval-augmented generation (MRAG). The first is knowledge bias: an LLM answers the same question differently depending on its language. The second is knowledge conflict: passages retrieved from collections in many languages contradict each other. The authors… 2. **[Blind Spot Navigation in Large Language Model Reasoning with Thought Space Explorer](https://md.research.elamur.ai/free/en/papers/zhang-2026-blind-spot-navigation-large-language/)** *(2026 · 3 citations)* Tree-like and multi-chain prompting methods such as ToT usually refine or extend reasoning paths the model has already produced. 3. **[Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mo-2026-agentic-conversational-search-contextualized-reasoning/)** *(2026 · 2 citations)* Multi-turn conversational search is usually handled by a fixed "rewrite, retrieve, generate" chain of separately trained components. 4. **[Instant Personalized Large Language Model Adaptation via Hypernetwork](https://md.research.elamur.ai/free/en/papers/tan-2026-instant-personalized-large-language-model/)** *(2026 · 2 citations)* Tailoring LLMs to individual users with parameter-efficient fine-tuning works well. However, the "One-PEFT-Per-User" (OPPU) approach trains a separate adapter for every person, which is too costly for millions of users or for preferences that change over time. The authors propose Profile-to-PEFT (P2P), which replaces… 5. **[MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/liu-2026-mtmcs-bench-evaluating-contextual-safety/)** *(2026 · 1 citation)* Most safety benchmarks for multimodal large language models (MLLMs) test one image–prompt pair at a time. They miss harmful intent that builds up over a conversation or that is stated early and then hidden behind innocent follow-ups. MTMCS-Bench fills this gap with three-turn dialogues grounded in COCO-style images.… 6. **[ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting](https://md.research.elamur.ai/free/en/papers/tian-2026-reattn-improving-attention-based-re/)** *(2026 · 1 citation)* Attention-based re-ranking scores candidate documents from an LLM's internal attention rather than from generated output. 7. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/)** *(2026 · 1 citation)* Multimodal LLMs are increasingly used as everyday assistants. Their answers can steer people into risky actions even when the user has no harmful intent. Most existing safety benchmarks target jailbreaks or explicit harm, and implicit-risk sets tend to be small or artificial. The authors introduce SaLAD, a benchmark… 8. **[A Dual-View Analysis of Multiple Languages in Colonial Newspapers](https://md.research.elamur.ai/free/en/papers/su-2026-dual-view-analysis-multiple-languages/)** *(2026)* Colonial-era newspapers record how racial categories were built and maintained, but they are hard to analyse computationally. Annotated data is scarce, OCR output is noisy, and the texts are multilingual and archaic. The authors study racialization from two complementary angles. ## All works 9 works of theirs in our library, the most cited first; 8 with a page here, the others link their original until we summarise them. 1. **[Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search ↗](https://aclanthology.org/2023.findings-emnlp.86/) Findings of the Association for Computational Linguistics: EMNLP 2023 · no summary yet**Kelong Mao et al.*2023 · 99 citations* 2. **[Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/qi-2026-language-coupled-reinforcement-learning-multilingual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Qi, Fengran Mo, Yufeng Chen, et al.*2026 · 5 citations* 3. **[Blind Spot Navigation in Large Language Model Reasoning with Thought Space Explorer](https://md.research.elamur.ai/free/en/papers/zhang-2026-blind-spot-navigation-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinghan Zhang, Fengran Mo, Tharindu Cyril Weerasooriya, et al.*2026 · 3 citations* 4. **[Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mo-2026-agentic-conversational-search-contextualized-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fengran Mo, Yifan Gao, Sha Li, et al.*2026 · 2 citations* 5. **[Instant Personalized Large Language Model Adaptation via Hypernetwork](https://md.research.elamur.ai/free/en/papers/tan-2026-instant-personalized-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoxuan Tan, Zixuan Zhang, Haoyang Wen, et al.*2026 · 2 citations* 6. **[MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/liu-2026-mtmcs-bench-evaluating-contextual-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Dongwhi Kim, Yixin Wan, et al.*2026 · 1 citation* 7. **[ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting](https://md.research.elamur.ai/free/en/papers/tian-2026-reattn-improving-attention-based-re/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxing Tian, Fengran Mo, Weixu Zhang, et al.*2026 · 1 citation* 8. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyue Lou, Xu Jinan, Jingyi Yin, et al.*2026 · 1 citation* 9. **[A Dual-View Analysis of Multiple Languages in Colonial Newspapers](https://md.research.elamur.ai/free/en/papers/su-2026-dual-view-analysis-multiple-languages/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhan Su, Xiaoya Chen, Fengran Mo, et al.*2026* ## Co-authors here 12 of 36 co-authors with a page, the most papers together first. - [Meng Jiang](https://md.research.elamur.ai/free/en/authors/meng-jiang/) ×4 - [Zhaoxuan Tan](https://md.research.elamur.ai/free/en/authors/zhaoxuan-tan/) ×3 - [Jian-Yun Nie](https://md.research.elamur.ai/free/en/authors/jian-yun-nie/) ×2 - [Kaiyu Huang](https://md.research.elamur.ai/free/en/authors/kaiyu-huang/) ×2 - [Xu Jinan](https://md.research.elamur.ai/free/en/authors/xu-jinan/) ×2 - [Zheyuan Liu](https://md.research.elamur.ai/free/en/authors/zheyuan-liu/) ×2 - [Dakuo Wang](https://md.research.elamur.ai/free/en/authors/dakuo-wang/) - [Dongjie Wang](https://md.research.elamur.ai/free/en/authors/dongjie-wang/) - [Hansi Zeng](https://md.research.elamur.ai/free/en/authors/hansi-zeng/) - [Haoyang Wen](https://md.research.elamur.ai/free/en/authors/haoyang-wen/) - [Jianshu Chen](https://md.research.elamur.ai/free/en/authors/jianshu-chen/) - [Jinghan Zhang](https://md.research.elamur.ai/free/en/authors/jinghan-zhang/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×7: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×7 - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - Findings of the Association for Computational Linguistics: EMNLP 2023 ## Cited by Papers of our library cite their works 57 times (of the 149,439 papers whose bibliographies we read); [13 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/fengran-mo/cited-by/). Updated 1 November 2026