---
title: "Who cites Manuel Faysse — page 2 — 409 papers of our library"
description: "409 papers of the Elamur Research library cite the works of Manuel Faysse, found in their bibliographies · page 2 of 2 · 101–121; the most cited first."
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---
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# Who cites Manuel Faysse

441 citations of their works from 409 papers of our library (of the 149,439 whose bibliographies we read) · 121 with a page here, the most cited first · page 2 of 2 · 101–121 · [← Manuel Faysse](https://md.research.elamur.ai/free/en/authors/manuel-faysse/)

[← prev](https://md.research.elamur.ai/free/en/authors/manuel-faysse/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/manuel-faysse/cited-by/) **2**

101. **[Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains](https://md.research.elamur.ai/free/en/papers/xiong-2026-lang2act-fine-grained-visual-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqi Xiong, Chunyi Peng, Zhipeng Xu, et al.*2026*
102. **[Language Proficiency as a Recoverable Dimension in Multilingual LLM Embeddings](https://md.research.elamur.ai/free/en/papers/wilkens-2026-language-proficiency-as-recoverable-dimension/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Rodrigo Wilkens*2026*
103. **[LLMs Meet Isolation Kernel: Lightweight, Learning-free Binary Embeddings for Fast Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2026-llms-meet-isolation-kernel-lightweight/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhibo Zhang, Yang Xu, Kai Ming Ting, et al.*2026*
104. [**LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answering arXiv:2607.02763**Nina Hosseini-Kivanani, Marco Matassoni, Alessio Brutti*2026*](https://md.research.elamur.ai/free/en/papers/hosseini-kivanani-2026-luxsqa-ask-me-luxembourgish-tts/)
105. [**LëtzCross: A Cross-Lingual Page-Level Benchmark for Multimodal Retrieval over Luxembourgish Documents arXiv:2608.21714**Omar El Bachyr, Fred Philippy, Laura Maria Bernardy, et al.*2026*](https://md.research.elamur.ai/free/en/papers/bachyr-2026-l-etzcross-cross-lingual-page/)
106. **[MAB-DQA: Addressing Query Aspect Importance in Document Question Answering with Multi-Armed Bandits](https://md.research.elamur.ai/free/en/papers/xiang-2026-mab-dqa-addressing-query-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Xiang, Yunshan Ma, Xiaoyu Du, et al.*2026*
107. [**MameLoshnLM: Yiddish Language Model and Evaluation Benchmark arXiv:2608.05850 · Proceedings of the Third Conference on Language Modeling (COLM 2026), 2026**Uri Katz, Omer Goldman, Tomasz Limisiewicz, et al.*2026*](https://md.research.elamur.ai/free/en/papers/katz-2026-mameloshnlm-yiddish-language-model-evaluation/)
108. **[MDocRAG-RL: Empowering Multi-Modal Document RAG via Complex Visual Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-mdocrag-rl-empowering-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongyu Wang*2026*
109. **[Modeling semantic association in self-paced reading with language model embeddings](https://md.research.elamur.ai/free/en/papers/ostergaard-2026-modeling-semantic-association-self-paced/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Sara Møller Østergaard, Kenneth Enevoldsen, Afra Alishahi, et al.*2026*
110. **[Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation](https://md.research.elamur.ai/free/en/papers/thellmann-2026-quantifying-impact-translation-errors-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Klaudia Thellmann, Bernhard Stadler, Michael Färber, et al.*2026*
111. **[Reading Time in the Wild: An Assessment of Readability Predictors Based on Naturally-Observed Reading Times](https://md.research.elamur.ai/free/en/papers/vaals-2026-reading-time-wild-assessment-readability/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sijbren van Vaals, Rik van Noord, Malvina Nissim*2026*
112. [**Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling arXiv:2604.28075**Ansar Aynetdinov, Patrick Haller, Alan Akbik*2026*](https://md.research.elamur.ai/free/en/papers/aynetdinov-2026-repetition-over-diversity-high-signal/)
113. **[SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation](https://md.research.elamur.ai/free/en/papers/suppa-2026-skmteb-slovak-massive-text-embedding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marek Suppa, Andrej Ridzik, Daniel Hládek, et al.*2026*
114. **[Small Can Be Beautiful in LLMs for SSH: a Case for Bulgarian](https://md.research.elamur.ai/free/en/papers/simov-2026-small-can-be-beautiful-llms/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Kiril Simov, Nikolay Paev, Petya Osenova, et al.*2026*
115. **[SwissGov-RSD: A Human-annotated, Cross-lingual Benchmark for Token-level Recognition of Semantic Differences Between Related Documents](https://md.research.elamur.ai/free/en/papers/wastl-2026-swissgov-rsd-human-annotated-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michelle Wastl, Jannis Vamvas, Rico Sennrich*2026*
116. **[Take It All: Ensemble Retrieval for Multimodal Evidence Aggregation](https://md.research.elamur.ai/free/en/papers/upravitelev-2026-take-it-all-ensemble-retrieval/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Max Upravitelev, Veronika Solopova, Premtim Sahitaj, et al.*2026*
117. **[The MaTOS Pipeline for the Translation of Scientific Abstracts on the HAL Platform](https://md.research.elamur.ai/free/en/papers/tsolakis-2026-matos-pipeline-translation-scientific-abstracts/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Panagiotis Tsolakis, Ziqian Peng, Laurent Romary, et al.*2026*
118. **[The Overlooked Role of Graded Relevance Thresholds in Multilingual Dense Retrieval](https://md.research.elamur.ai/free/en/papers/wullach-2026-overlooked-role-graded-relevance-thresholds/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tomer Wullach, Ori Shapira, Amir David Nissan Cohen*2026*
119. **[Training Biomedical Retrievers From Large-Scale Citation Contexts](https://md.research.elamur.ai/free/en/papers/wang-2026-training-biomedical-retrievers-large-scale/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Xing David Wang, Duy Le Thanh, Ulf Leser*2026*
120. **[When Tables Go Crazy: Evaluating Multimodal Models on French Financial Documents](https://md.research.elamur.ai/free/en/papers/mouilleron-2026-when-tables-go-crazy-evaluating/) [Financial Narrative Processing Workshop](https://md.research.elamur.ai/free/en/venues/fnp/)**Virginie Mouilleron, Théo Lasnier, Anna Mosolova, et al.*2026*
121. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*

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