---
title: "Who cites Paul Kishan — page 9 — 4,416 citing papers"
description: "4,416 papers of the Elamur Research library cite the works of Paul Kishan Rubenstein, found in their bibliographies · page 9 of 12 · 801–900…"
canonical: "https://research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/9/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/9/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Paul Kishan Rubenstein](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/) / [cited by](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/) / page 9

# Who cites Paul Kishan Rubenstein

4,747 citations of their works from 4,416 papers of our library (of the 149,439 whose bibliographies we read) · 1,116 with a page here, the most cited first · page 9 of 12 · 801–900 · [← Paul Kishan Rubenstein](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/)

[← prev](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/8/) [1](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/) … [8](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/8/) **9** [10](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/11/) [12](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/12/) [next →](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/10/)

801. **[AI Safety Lost in Translation: Evaluating the Effectiveness of English-Italian Cross-Lingual LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/wu-2026-ai-safety-lost-translation-evaluating/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Alessio Wu, Martim Brandao*2026*
802. **[Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/qian-2026-aligning-backchannel-dialogue-context-representations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Livia Qian, Gabriel Skantze*2026*
803. **[Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization](https://md.research.elamur.ai/free/en/papers/rahman-2026-aligning-text-code-vision-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mizanur Rahman, Mohammed Saidul Islam, Md Tahmid Rahman Laskar, et al.*2026*
804. **[An Answer is just the Start: Related Insight Generation for Open-Ended Document-Grounded QA](https://md.research.elamur.ai/free/en/papers/sharma-2026-answer-is-just-start-related/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Saransh Sharma, Pritika Ramu, Aparna Garimella, et al.*2026*
805. **[An Evaluation of Classifiers for Mapping Generative LLM Responses to Answer Options of Multiple-choice Questionnaires](https://md.research.elamur.ai/free/en/papers/stroligo-2026-evaluation-classifiers-mapping-generative-llm/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alisea Stroligo, Anna Shamray, Julian Schelb, et al.*2026*
806. **[AnswerCarefully: Creating a Dataset for LLM Safety in Japanese](https://md.research.elamur.ai/free/en/papers/suzuki-2026-answercarefully-creating-dataset-llm-safety/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hisami Suzuki, Satoru Katsumata, Takashi Kodama, et al.*2026*
807. **[Applicability Condition Extraction for Therapeutic Drug-Disease Relations](https://md.research.elamur.ai/free/en/papers/luo-2026-applicability-condition-extraction-therapeutic-drug/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guanting Luo, Noriki Nishida, Yuji Matsumoto, et al.*2026*
808. [**Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models**Mohamed Adel, Bashar Alhafni, Nizar Habash*2026*](https://md.research.elamur.ai/free/en/papers/adel-2026-arabic-morphosyntactic-tagging-dependency-parsing/)
809. [**ArabicNumBench: Evaluating Arabic Number Reading in Large Language Models arXiv:2602.18776**Anas Alhumud, Abdulaziz Alhammadi, Muhammad Badruddin Khan*2026*](https://md.research.elamur.ai/free/en/papers/alhumud-2026-arabicnumbench-evaluating-arabic-number-reading/)
810. [**ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation arXiv:2606.10765**Khaled Elhady, Omar Kallas, Nizar Habash, et al.*2026*](https://md.research.elamur.ai/free/en/papers/elhady-2026-arabigee-hierarchical-taxonomy-arabic-grammatical/)
811. [**Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation arXiv:2604.03395**Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/alqadi-2026-arabic-benchmarks-reliable-qimma-s/)
812. **[Ascending the Infinite Ladder: Benchmarking Spatial Deformation Reasoning in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-ascending-infinite-ladder-benchmarking-spatial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahuan Zhang, Shunwen Bai, Tianheng Wang, et al.*2026*
813. **[AssamLegalTrans: A Parallel Corpus, Benchmark and Analysis for English-Assamese Machine Translation of Legal Judgments](https://md.research.elamur.ai/free/en/papers/singh-2026-assamlegaltrans-parallel-corpus-benchmark-analysis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Telem Joyson Singh, Hemanta Baruah, Sanasam Ranbir Singh, et al.*2026*
814. **[Automatic and Reliable Evaluation for Academic Caption-to-Figure Generation with LMMs](https://md.research.elamur.ai/free/en/papers/ye-2026-automatic-reliable-evaluation-academic-caption/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanghui Ye, Huan Zhao, Qin Zhu, et al.*2026*
815. **[AVA: Attentive VLM Agent for Mastering StarCraft II](https://md.research.elamur.ai/free/en/papers/ma-2026-ava-attentive-vlm-agent-mastering/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weiyu Ma, Yuqian Fu, Zecheng Zhang, et al.*2026*
816. **[Benchmarking and Mitigating the Impact of Noisy User Prompts in Medical VLMs via Cross-Modal Reflection](https://md.research.elamur.ai/free/en/papers/xue-2026-benchmarking-mitigating-impact-noisy-user/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhiyu Xue, Reza Abbasi-Asl, Ramtin Pedarsani*2026*
817. **[Benchmarking Deflection and Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/moratelli-2026-benchmarking-deflection-hallucination-large-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nicholas Moratelli, Christopher Davis, Leonardo F. R. Ribeiro, et al.*2026*
818. **[Benchmarking Web Agent Safety under E-commerce Deceptive Interfaces](https://md.research.elamur.ai/free/en/papers/shi-2026-benchmarking-web-agent-safety-under/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijing Shi, Meng Fang, Ling Chen*2026*
819. **[Beyond Bias Scores: Unmasking Vacuous Neutrality in Small Language Models](https://md.research.elamur.ai/free/en/papers/manduru-2026-beyond-bias-scores-unmasking-vacuous/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sumanth Manduru, Carlotta Domeniconi*2026*
820. **[Beyond Modality Collapse: Taming Guided Modality Entropy for Omni-modal Emotion Reasoning](https://md.research.elamur.ai/free/en/papers/zhao-2026-beyond-modality-collapse-taming-guided/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xian Zhao, Rui Hu, Yuxiang Zhang, et al.*2026*
821. **[Beyond Query Memorization: Large Language Model Routing with Query Decomposition and Historical Matching](https://md.research.elamur.ai/free/en/papers/lv-2026-beyond-query-memorization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Lv, Jingbo Sun, Jianwei Lv, et al.*2026*
822. **[Beyond Single View: A Comprehensive Benchmark for Medical Multimodal Large Language Models on Multi-Image Understanding](https://md.research.elamur.ai/free/en/papers/xu-2026-beyond-single-view-comprehensive-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dexuan Xu, Yuan Jiayin, Jianing Wang, et al.*2026*
823. **[Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-static-rules-automated-discovery/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanqing Wang, Yongdong Chi, Jian Yang, et al.*2026*
824. **[Black-Box Membership Inference Attacks for Video Training Data in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-black-box-membership-inference-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinrui Wang, Zhenfeng Gao, Wendan Wang, et al.*2026*
825. **[bLLeQA: Benchmarking LLMs for Grounded Legal Question-Answering in French and Dutch](https://md.research.elamur.ai/free/en/papers/banar-2026-blleqa-benchmarking-llms-grounded-legal/) [Workshop on Towards Knowledgeable Foundation Models](https://md.research.elamur.ai/free/en/venues/knowfm/)**Nikolay Banar, Ehsan Lotfi, Jens Van Nooten, et al.*2026*
826. **[Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation](https://md.research.elamur.ai/free/en/papers/miandoab-2026-breaking-benchmark-revealing-llm-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kaveh Eskandari Miandoab, Mahammed Kamruzzaman, Arshia Gharooni, et al.*2026*
827. [**Bridging the English-Arabic Medical Knowledge Gap: Targeted Low-Rank Adaptation via Causal Layer Selection arXiv:2608.00207 · Findings of the Association for Computational Linguistics: EMNLP 2026**Chaimae Abouzahir, Musa Khan, Hala Ali-Hassan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abouzahir-2026-bridging-english-arabic-medical-knowledge/)
828. **[CAMO: An Agentic Framework for Automated Causal Discovery from Micro Behaviors to Macro Emergence in LLM Agent Simulations](https://md.research.elamur.ai/free/en/papers/yu-2026-camo-agentic-framework-automated-causal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangning Yu, Yuwei Guo, Yuqi Hou, et al.*2026*
829. **[Can LLMs Learn to Map the World from Local Descriptions?](https://md.research.elamur.ai/free/en/papers/xia-2026-can-llms-learn-map-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sirui Xia, Aili Chen, Xintao Wang, et al.*2026*
830. **[Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical Reasoning](https://md.research.elamur.ai/free/en/papers/merenda-2026-can-llms-reason-like-doctors/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Flavio Merenda, Jose Manuel Gomez-Perez, German Rigau*2026*
831. **[CAR: Empowering Agents with Dynamic Tool Synthesis and Global Trajectory Rectification](https://md.research.elamur.ai/free/en/papers/wang-2026-car-empowering-agents-dynamic-tool/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Wang, Xu Wang, Zhiyuan Fu, et al.*2026*
832. **[CEMT:Controllable Element-Oriented Machine Translation via Structured Linguistic Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2026-cemt-controllable-element-oriented-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingling Shi, Haoyu Jin, Ruiyu Fang, et al.*2026*
833. **[Chart-MRAG: Benchmarking Multimodal Retrieval Augmented Generation on Chart-based Documents](https://md.research.elamur.ai/free/en/papers/ymyang-2026-chart-mrag-benchmarking-multimodal-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ymyang, Jiang Zhong, Li Jin, et al.*2026*
834. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026*
835. **[ChildEval:WHEN LARGE LANGUAGE MODELS MEET CHILDREN'S PERSONALITIES](https://md.research.elamur.ai/free/en/papers/luo-2026-childeval-when-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanyan Luo, Xue Han, Chunxu Zhao, et al.*2026*
836. **[CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis](https://md.research.elamur.ai/free/en/papers/xu-2026-cnsocialdepress-chinese-social-media-dataset/) [Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium](https://md.research.elamur.ai/free/en/venues/rapid/)**Jinyuan Xu, Tian Lan, Xintao Yu, et al.*2026*
837. **[code-transformed: The Influence of Large Language Models on Code](https://md.research.elamur.ai/free/en/papers/xu-2026-code-transformed-influence-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuliang Xu, Siming Huang, Mingmeng Geng, et al.*2026*
838. **[CodeGuard: Improving LLM Guardrails in CS Education](https://md.research.elamur.ai/free/en/papers/raihan-2026-codeguard-improving-llm-guardrails-cs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nishat Raihan, Noah Erdachew, Jayoti Devi, et al.*2026*
839. **[CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution](https://md.research.elamur.ai/free/en/papers/yang-2026-coevolve-training-llm-agents-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shidong Yang, Ziyu Ma, Tongwen Huang, et al.*2026*
840. **[CogEvolve: A Multimodal Benchmark for Evaluating Relational Reasoning in Semantic Extension](https://md.research.elamur.ai/free/en/papers/zeng-2026-cogevolve-multimodal-benchmark-evaluating-relational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingjie Zeng, Huayang Li, Liang Yang, et al.*2026*
841. **[Common Sense vs. Morality: The Curious Case of Narrative Focus Bias in LLMs](https://md.research.elamur.ai/free/en/papers/purkayastha-2026-common-sense-vs-morality-curious/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Saugata Purkayastha, Pranav Kushare, Pragya Paramita Pal, et al.*2026*
842. [**Comparing and Modeling Argumentation in German Political Communication across Arenas arXiv:2608.00288**Nina Vikhrova, Johannes Kuhling, Sebastian Haunss, et al.*2026*](https://md.research.elamur.ai/free/en/papers/vikhrova-2026-comparing-modeling-argumentation-german-political/)
843. **[Comparing Approaches to Automatic Summarization in Less-Resourced Languages](https://md.research.elamur.ai/free/en/papers/michel-2026-comparing-approaches-automatic-summarization-less/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Chester Palen-Michel, Constantine Lignos*2026*
844. **[Compressing Language Models for Specialized Domains](https://md.research.elamur.ai/free/en/papers/williams-2026-compressing-language-models-specialized-domains/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Miles Williams, George Chrysostomou, Vitor Amancio Jeronymo, et al.*2026*
845. **[CompTab: A Comprehensive Benchmark for Real-World TableQA with Complex Reasoning and Irregular Tables](https://md.research.elamur.ai/free/en/papers/yang-2026-comptab-comprehensive-benchmark-real-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Yang, Wei Du, Jie Wang, et al.*2026*
846. **[Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.*2026*
847. **[Construction and Analysis of Japanese Parent-Child Dialogic Reading Corpus for Conversational Agents](https://md.research.elamur.ai/free/en/papers/nakagi-2026-construction-analysis-japanese-parent-child/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuko Nakagi, Yuya Chiba, Sanae Fujita, et al.*2026*
848. **[CoopValue: Revealing LLM Value Preferences Through Multi-Agent Cooperation](https://md.research.elamur.ai/free/en/papers/tang-2026-coopvalue-revealing-llm-value-preferences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zee Hen Tang, Mi-Yen Yeh*2026*
849. **[CoPA: Benchmarking Personalized Question Answering with Data-Informed Cognitive Factors](https://md.research.elamur.ai/free/en/papers/su-2026-copa-benchmarking-personalized-question-answering/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hang Su, Zequn Liu, Chen Hu, et al.*2026*
850. **[CoreELM: An Open-Source Framework for Aligning Large Language Models to Embedding Spaces](https://md.research.elamur.ai/free/en/papers/ondov-2026-coreelm-open-source-framework-aligning/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Brian Ondov, Chia-Hsuan Chang, Yujia Zhou, et al.*2026*
851. **[Corpus and Baselines for Distinguishing Authentic, AI-Generated, and AI-Enhanced Resumes](https://md.research.elamur.ai/free/en/papers/loizidou-2026-corpus-baselines-distinguishing-authentic-ai/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Andrea Loizidou, Anshu Kiran Sharma, Adrian Esquivel, et al.*2026*
852. **[Counterfactual Auditing of Cross-Cultural Variation in LLM-Generated Medical Advice](https://md.research.elamur.ai/free/en/papers/yoo-2026-counterfactual-auditing-cross-cultural-variation/) [Workshop on Stereotypes Across Cultures in Language Technologies](https://md.research.elamur.ai/free/en/venues/stereacult/)**Hyunwoo Yoo, Gail Rosen*2026*
853. **[Cross-Lingual Bias in Large Language Models: A Comparative Analysis of English and Swahili](https://md.research.elamur.ai/free/en/papers/zhang-2026-cross-lingual-bias-large-language/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Ruolei Zhang, Teddy Njuguna, Yue Feng*2026*
854. **[CSI: An Investigative Multi-Agent Framework for Explainable Short Video Fake News Detection](https://md.research.elamur.ai/free/en/papers/wang-2026-csi-investigative-multi-agent-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxin Wang, Yang Yang, Huaiwen Zhang*2026*
855. **[Cultural and Knowledge Biases in LLMs through the Lens of Entity-Aware Machine Translation](https://md.research.elamur.ai/free/en/papers/xu-2026-cultural-knowledge-biases-llms-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lu Xu, Luca Moroni, Roberto Navigli*2026*
856. **[Curriculum Learning based Hierarchical Scoring and Analysis Framework for Question Answering Task Evaluation](https://md.research.elamur.ai/free/en/papers/wu-2026-curriculum-learning-based-hierarchical-scoring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiong Wu, Tan Yue, Jianxin Liang, et al.*2026*
857. **[D-Artemis: A Deliberative Cognitive Framework for Mobile GUI Multi-Agents](https://md.research.elamur.ai/free/en/papers/mi-2026-d-artemis-deliberative-cognitive-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongze Mi, Yibo Feng, WenJie Lu, et al.*2026*
858. **[DAC-Bench: A Decision-Aware Benchmark for Compositional Mobile GUI Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2026-dac-bench-decision-aware-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuqing Zhang, Honghui Sheng, Xueyu Hu, et al.*2026*
859. **[Dashboard2Code: Evaluating Multimodal Models on Reconstructing Interactive Dashboards](https://md.research.elamur.ai/free/en/papers/niu-2026-dashboard2code-evaluating-multimodal-models-reconstructing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianhao Niu, Ziyu Han, Qiguang Chen, et al.*2026*
860. **[Data-Centric Approach at the LoResMT 2026 Turkic Translation Challenge: Russian-Kyrgyz](https://md.research.elamur.ai/free/en/papers/novokshanov-2026-data-centric-approach-loresmt-2026/) [Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT)](https://md.research.elamur.ai/free/en/venues/loresmt/)**Dmitry Novokshanov*2026*
861. **[DeepPavlov Strikes Back: A Toolkit for Improving LLM Reliability and Trustworthiness](https://md.research.elamur.ai/free/en/papers/nikolaev-2026-deeppavlov-strikes-back-toolkit-improving/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Evgenii Nikolaev, Timur Ionov, Anna Korzanova, et al.*2026*
862. **[Detecting Hallucinations in Authentic LLM–Human Interactions](https://md.research.elamur.ai/free/en/papers/ren-2026-detecting-hallucinations-authentic-llm-human/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yujie Ren, Niklas Gruhlke, Anne Lauscher*2026*
863. **[Detecting Latin in Historical Books with Large Language Models: A Multimodal Benchmark](https://md.research.elamur.ai/free/en/papers/wu-2026-detecting-latin-historical-books-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu Wu, Ke Shu, Jonas Fischer, et al.*2026*
864. **[Detecting What Queries Seek: Steering LLM Safety with FFN Output Activation Monitoring](https://md.research.elamur.ai/free/en/papers/luo-2026-detecting-what-queries-seek-steering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaohao Luo, Ying Wei, Rui Zhao*2026*
865. **[DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deference](https://md.research.elamur.ai/free/en/papers/rabbani-2026-dialdefer-framework-detecting-mitigating-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parisa Rabbani, Priyam Sahoo, Ruben Mathew, et al.*2026*
866. [**DialectLLM: A Dialect-Aware Dialogue Generation Framework Beyond Standard American English arXiv:2601.22888**Jio Oh, Paul Vicinanza, Thomas Butler, et al.*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-dialectllm-dialect-aware-dialog-ue/)
867. [**DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation arXiv:2607.07669**Jordan Painter, Dipankar Srirag, Adarsh Kappiyath, et al.*2026*](https://md.research.elamur.ai/free/en/papers/painter-2026-diallm-investigation-robustness-generation-gap/)
868. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Zhou, Xuxin Cheng, Shiwan Zhao, et al.*2026*
869. **[DisCal: Distribution-Aware Calibration for Mathematical Reasoning Under Character-Level Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-discal-distribution-aware-calibration-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Zhang, Jiawei Zhang, Cong Gao, et al.*2026*
870. **[Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Study](https://md.research.elamur.ai/free/en/papers/ziletti-2026-disentangling-ambiguity-instability-large-language/) [Workshop on Clinical Natural Language Processing (Clinical NLP) @ LREC](https://md.research.elamur.ai/free/en/venues/clinicalnlp/)**Angelo Ziletti, Leonardo D'Ambrosi*2026*
871. **[Distilling Examples into Task Instructions: Enhanced In-Context Learning for Real-World B2B Conversations](https://md.research.elamur.ai/free/en/papers/rotman-2026-distilling-examples-into-task-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guy Rotman, Adi Kopilov, Danit Berger Zalmanson, et al.*2026*
872. **[Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?](https://md.research.elamur.ai/free/en/papers/modica-2026-do-factual-recall-mechanisms-carry/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Luca Modica, Filip Landin, Mehrdad Farahani, et al.*2026*
873. **[Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026*
874. **[Doc-V*: Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA](https://md.research.elamur.ai/free/en/papers/zheng-2026-doc-v-coarse-fine-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanlei Zheng, Pei Fu, Hang Li, et al.*2026*
875. [**Don't ‘Well, Actually' Me Unless You Know What You're Talking About: Weak Presupposition Verification Degrades General QA Performance arXiv:2608.06539**Shenran Wang, Vered Shwartz, Hila Gonen*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-well-actually-me/)
876. **[DOSE: Data Selection for Multi-Modal LLMs via Off-the-Shelf Models](https://md.research.elamur.ai/free/en/papers/wu-2026-dose-data-selection-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Biao Wu, Yiwu Zhong, Meng Fang, et al.*2026*
877. **[D²-RAG: Dual-Decision Retrieval-Augmented Generation via Multi-Dimensional Uncertainty and Utility-Aware Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-d-2-rag-dual-decision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinshuo Zhang, Xiaoding Zhou, Weiyu Zhang, et al.*2026*
878. **[D²Plan: Dual-Agent Dynamic Global Planning for Complex Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/luo-2026-d-2-plan-dual-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangcheng Luo, Tinglang Wu, Yansong Feng*2026*
879. **[Efficient Low-Resource Language Adaptation via Multi-Source Dynamic Logit Fusion](https://md.research.elamur.ai/free/en/papers/zhang-2026-efficient-low-resource-language-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chen Zhang, Jiuheng Lin, Zhiyuan Liao, et al.*2026*
880. **[EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressions](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*
881. **[EmoMM: Benchmarking and Steering MLLM for Multimodal Emotion Recognition under Conflict and Missingness](https://md.research.elamur.ai/free/en/papers/sun-2026-emomm-benchmarking-steering-mllm-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yueru Sun, Yimeng Zhang, Haoyu Gu, et al.*2026*
882. **[EncouRAGe: Evaluating RAG Local, Reliable, and Efficient](https://md.research.elamur.ai/free/en/papers/strich-2026-encourage-evaluating-rag-local-reliable/) [Workshop on Multilingual Report Generation via Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/venues/rag4reports/)**Jan Strich, Martin Semmann, Chris Biemann*2026*
883. [**English is Not All You Need: Systematically Exploring the Role of Multilinguality in LLM Post-Training arXiv:2604.13286**Mehak Dhaliwal, Shashwat Chaurasia, Yao Qin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/dhaliwal-2026-english-all-need-systematically-exploring/)
884. **[EQUIP: EQUivariant preserving In-Place updates for Efficient Token Pruning](https://md.research.elamur.ai/free/en/papers/ramachandran-2026-equip-equivariant-preserving-place-updates/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arun Ramachandran, R Govindarajan, Murali Annavaram, et al.*2026*
885. [**Evaluating Communicative Belief Updates in Large Language Models via Implicature Recognition and Cancellation arXiv:2607.25094**Cesare Spinoso-Di Piano, Verna Dankers, Marius Mosbach, et al.*2026*](https://md.research.elamur.ai/free/en/papers/piano-2026-evaluating-communicative-belief-updates-large/)
886. **[Evaluating Generative Large Language Models for Portuguese Scientific Information Extraction](https://md.research.elamur.ai/free/en/papers/pinto-2026-evaluating-generative-large-language-models/) [Natural Scientific Language Processing (NSLP) @ LREC](https://md.research.elamur.ai/free/en/venues/nslp/)**Tomás Pinto, Catarina Silva, Hugo Goncalo Oliveira*2026*
887. **[Evaluating the Effect of Question Wording Variations on Answer Consistency in Large Language Models](https://md.research.elamur.ai/free/en/papers/takayama-2026-evaluating-effect-question-wording-variations/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Junya Takayama, Masaya Ohagi, Tomoya Mizumoto, et al.*2026*
888. **[Experience-driven Multi-turn Reinforcement Learning for GUI Agents](https://md.research.elamur.ai/free/en/papers/lu-2026-experience-driven-multi-turn-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxi Lu, Jiabo Ye, Fei Tang, et al.*2026*
889. **[ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images](https://md.research.elamur.ai/free/en/papers/sibue-2026-exstructiny-benchmark-schema-variable-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, et al.*2026*
890. **[Extending Czech Aspect-Based Sentiment Analysis with Opinion Terms: Dataset and LLM Benchmarks](https://md.research.elamur.ai/free/en/papers/smid-2026-extending-czech-aspect-based-sentiment/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jakub Šmíd, Pavel Priban, Pavel Kral*2026*
891. **[FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text Generation](https://md.research.elamur.ai/free/en/papers/shan-2026-factverse-benchmark-factual-consistency-interleaved/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yubo Shan, Kun Zhang, Qiming Xu, et al.*2026*
892. **[FADE: Probing the Limits of VLMs on fine-grained OCR](https://md.research.elamur.ai/free/en/papers/shah-2026-fade-probing-limits-vlms-fine/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Deep Shah, Nehal Kathrotia, Sanket Badhe*2026*
893. **[Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale](https://md.research.elamur.ai/free/en/papers/tu-2026-fico-evaluating-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.*2026*
894. **[FINEST: Improving LLM Responses to Sensitive Topics Through Fine-Grained Evaluation](https://md.research.elamur.ai/free/en/papers/oh-2026-finest-improving-llm-responses-sensitive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Juhyun Oh, Nayeon Lee, Chani Jung, et al.*2026*
895. **[From Benchmarks to Skills: Low-Rank Factors for LLM Evaluation](https://md.research.elamur.ai/free/en/papers/maimon-2026-benchmarks-skills-low-rank-factors/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aviya Maimon, Amir David Nisan Cohen, Gal Vishne, et al.*2026*
896. **[From Bones to Rocks: A Systematic Evaluation of Specialized Definition Generation for Portuguese](https://md.research.elamur.ai/free/en/papers/nunes-2026-bones-rocks-systematic-evaluation-specialized/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rafael Oleques Nunes, Dennis Giovani Balreira, Joel Luís Carbonera*2026*
897. **[From Detection to Understanding: Multi-Turn Reasoning for Video Misinformation Analysis](https://md.research.elamur.ai/free/en/papers/zeng-2026-detection-understanding-multi-turn-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhi Zeng, Jiaying Wu, Minnan Luo, et al.*2026*
898. **[From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning](https://md.research.elamur.ai/free/en/papers/wu-2026-experience-skill-multi-agent-generative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beining Wu, Fuyou Mao, Jiong Lin, et al.*2026*
899. **[From Questions to Assessment Tuples: A Multi-Agent Framework with Bloom-Specialized Agents and Automated Verification](https://md.research.elamur.ai/free/en/papers/wong-2026-questions-assessment-tuples-multi-agent/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Gee-Lyle Wong, Runcong Zhao, Yulan He, et al.*2026*
900. **[From Tokens to Steps: Verification-Aware Speculative Decoding for Efficient Multi-Step Reasoning](https://md.research.elamur.ai/free/en/papers/purohit-2026-tokens-steps-verification-aware-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kiran Purohit, Ramasuri Narayanam, Soumyabrata Pal*2026*

[← prev](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/8/) [1](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/) … [8](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/8/) **9** [10](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/11/) [12](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/12/) [next →](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/cited-by/page/10/)

- [← back to](https://md.research.elamur.ai/free/en/authors/paul-kishan-rubenstein/) — Paul Kishan Rubenstein
