---
title: "Who cites Sertan Girgin — page 10 — 5,182 papers of our library"
description: "5,182 papers of the Elamur Research library cite the works of Sertan Girgin, found in their bibliographies · page 10 of 13 · 901–1000; the most…"
canonical: "https://research.elamur.ai/free/en/authors/sertan-girgin/cited-by/page/10/"
---
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# Who cites Sertan Girgin

5,745 citations of their works from 5,182 papers of our library (of the 149,439 whose bibliographies we read) · 1,262 with a page here, the most cited first · page 10 of 13 · 901–1000 · [← Sertan Girgin](https://md.research.elamur.ai/free/en/authors/sertan-girgin/)

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901. [**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/)
902. **[Calibrating Inference Time Alignment with Sequence-level Risk Accumulation](https://md.research.elamur.ai/free/en/papers/tan-2026-calibrating-inference-time-alignment-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shanwen Tan, Ziyang Dong, Wei Ju, et al.*2026*
903. **[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*
904. **[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*
905. **[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*
906. **[CaPEdit: Capability-Preserving Lifelong Knowledge Editing For Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-capedit-capability-preserving-lifelong-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Song-Li Wu, Zhaocheng Du, Xianquan Wang, et al.*2026*
907. **[ChemReason-Bench: Benchmarking Large Language Models for Procedural Reasoning in Experimental Chemistry](https://md.research.elamur.ai/free/en/papers/zhang-2026-chemreason-bench-benchmarking-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinwei Zhang, Xucheng Liang, Yu Zhang, et al.*2026*
908. **[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*
909. **[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*
910. **[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*
911. **[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*
912. **[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*
913. **[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*
914. **[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*
915. **[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*
916. [**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/)
917. **[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*
918. **[Comprehensive Benchmarking of Long-Form Speech Generation in Diverse Scenarios](https://md.research.elamur.ai/free/en/papers/pan-2026-comprehensive-benchmarking-long-form-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Changhao Pan, Rui Yang, Han Wang, et al.*2026*
919. **[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*
920. **[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*
921. **[Computational Narrative Understanding for Expressive Text-to-Speech](https://md.research.elamur.ai/free/en/papers/michel-2026-computational-narrative-understanding-expressive-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gaspard Michel, Elena V. Epure, Christophe Cerisara*2026*
922. **[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*
923. **[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*
924. **[Continuous Interpretive Steering for Scalar Diversity](https://md.research.elamur.ai/free/en/papers/cho-2026-continuous-interpretive-steering-scalar-diversity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ye-eun Cho*2026*
925. **[CoopQ: Cooperative Game Inspired Layerwise Mixed Precision Quantization for LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-coopq-cooperative-game-inspired-layerwise/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junchen Zhao, Ali Derakhshan, Jayden Hyman, et al.*2026*
926. **[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*
927. **[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*
928. **[CORE: Measuring Multi-Agent LLM Interaction Quality under Game-Theoretic Pressures](https://md.research.elamur.ai/free/en/papers/pandey-2026-core-measuring-multi-agent-llm/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Punya Syon Pandey, Yongjin Yang, Jiarui Liu, et al.*2026*
929. **[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*
930. **[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*
931. **[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*
932. **[Counterspeech Generation using Small Language Models](https://md.research.elamur.ai/free/en/papers/muhammad-2026-counterspeech-generation-small-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abubakar Sadiq Muhammad, Simona Frenda, Gavin Abercrombie*2026*
933. **[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*
934. **[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*
935. **[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*
936. **[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*
937. **[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*
938. **[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*
939. **[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*
940. **[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*
941. **[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*
942. **[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*
943. **[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*
944. [**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/)
945. [**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/)
946. **[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*
947. **[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*
948. **[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*
949. [**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/)
950. **[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*
951. **[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*
952. **[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*
953. **[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*
954. **[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*
955. **[Embracing Anisotropy: Turning Massive Activations into Interpretable Control Knobs for Large Language Models](https://md.research.elamur.ai/free/en/papers/roh-2026-embracing-anisotropy-turning-massive-activations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youngji Roh, Hyunjin Cho, Jaehyung Kim*2026*
956. **[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*
957. [**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/)
958. **[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*
959. [**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/)
960. **[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*
961. **[Evaluating Hierarchical Aggregation and LLM-Based Matching for Synset Selection in Ancient Greek](https://md.research.elamur.ai/free/en/papers/villa-2026-evaluating-hierarchical-aggregation-llm-based/) [Workshop on Language Technologies for Historical and Ancient Languages @ LREC](https://md.research.elamur.ai/free/en/venues/lt4hala/)**Luca Brigada Villa, Marco Passarotti, Chiara Zanchi, et al.*2026*
962. **[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*
963. **[Evaluating the Expressive Appropriateness of Speech in Rich Contexts](https://md.research.elamur.ai/free/en/papers/wang-2026-evaluating-expressive-appropriateness-speech-rich/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianrui Wang, Ziyang Ma, Yizhou Peng, et al.*2026*
964. [**Evaluating the Usage of African-American Vernacular English in Large Language Models arXiv:2602.21485**Deja Dunlap, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/dunlap-2026-evaluating-usage-african-american-vernacular/)
965. **[Evaluation Drift in LLM Personality Induction: Are We Moving the Goalpost?](https://md.research.elamur.ai/free/en/papers/rajput-2026-evaluation-drift-llm-personality-induction/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Prateek Kumar Rajput, Yewei Song, Iyiola Emmanuel Olatunji, et al.*2026*
966. **[Event Detection with a Context-Aware Encoder and LoRA for Improved Performance on Long-Tailed Classes](https://md.research.elamur.ai/free/en/papers/monsur-2026-event-detection-context-aware-encoder/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abdullah Al Monsur, Nitesh Vamshi Bommisetty, Gene Louis Kim*2026*
967. **[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*
968. **[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*
969. **[F-Actor: Controllable Conversational Behavior in Full-Duplex Models](https://md.research.elamur.ai/free/en/papers/zufle-2026-f-actor-controllable-conversational-behavior/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Maike Züfle, Ondrej Klejch, Nicholas Sanders, et al.*2026*
970. **[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*
971. **[Federated LoRA Fine-Tuning with Pipelined Error-Mitigated Aggregation and Matrix-Wise Freezing](https://md.research.elamur.ai/free/en/papers/wang-2026-federated-lora-fine-tuning-pipelined/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Wang, Xiong Wang, Yuqing Li, et al.*2026*
972. **[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*
973. **[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*
974. **[FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models](https://md.research.elamur.ai/free/en/papers/weng-2026-finesteer-unified-framework-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixuan Weng, Jinghuai Zhang, Kunlin Cai, et al.*2026*
975. **[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*
976. **[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*
977. **[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*
978. **[From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-insight-action-novel-framework-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ling Shi, Xinwei Wu, Xiaohu Zhao, et al.*2026*
979. **[From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?](https://md.research.elamur.ai/free/en/papers/mueller-2026-isolation-entanglement-when-do-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aaron Mueller, Andrew Lee, Shruti Joshi, et al.*2026*
980. **[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*
981. **[From Traditional Taggers to LLMs: A Comparative Study of POS Tagging for Medieval Romance Languages](https://md.research.elamur.ai/free/en/papers/schoffel-2026-traditional-taggers-llms-comparative-study/) [International Conference on Natural Language Processing for the Digital Humanities](https://md.research.elamur.ai/free/en/venues/nlp4dh/)**Matthias Schöffel, Esteban Garces Arias*2026*
982. **[GaLa: Hypergraph-Guided Visual Language Models for Procedural Planning](https://md.research.elamur.ai/free/en/papers/wang-2026-gala-hypergraph-guided-visual-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kun Wang, Li Yiming, Mingcheng Qu, et al.*2026*
983. **[GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-gameplayqa-benchmarking-framework-decision-dense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunzhe Wang, Runhui Xu, Kexin Zheng, et al.*2026*
984. **[Gender Disparities in LLM-Based Intimate Partner Violence Detection](https://md.research.elamur.ai/free/en/papers/prama-2026-gender-disparities-llm-based-intimate/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Tabia Tanzin Prama, Mikaela Irene Fudolig, Abigail M. Crocker, et al.*2026*
985. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
986. **[GenProve: Learning to Generate Text with Fine-Grained Provenance](https://md.research.elamur.ai/free/en/papers/wei-2026-genprove-learning-generate-text-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingxuan Wei, Xingyue Wang, Yanghaoyu Liao, et al.*2026*
987. **[GeoRC: A Benchmark for Geolocation Reasoning Chains](https://md.research.elamur.ai/free/en/papers/talreja-2026-georc-benchmark-geolocation-reasoning-chains/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohit Talreja, Joshua Diao, Jim James, et al.*2026*
988. **[GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026*
989. **[Global vs. Local Sentence Embeddings for Brazilian Portuguese: Revisiting Monolingual Models in the Age of Foundation Models](https://md.research.elamur.ai/free/en/papers/peixoto-2026-global-vs-local-sentence-embeddings/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Matheus Peixoto, Guilherme Silva, Giacomo Figueredo, et al.*2026*
990. **[GlossMATE: Multi-Agent Translator Explanations for Glosses](https://md.research.elamur.ai/free/en/papers/yang-2026-glossmate-multi-agent-translator-explanations/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Changbing Yang, Patrick Littell, Gabriel Bernier-Colborne, et al.*2026*
991. [**GradeLegal: Automated Grading for German Legal Cases arXiv:2605.21076**Abdullah Al Zubaer, Lorenz Wendlinger, Simon Alexander Nonn, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zubaer-2026-gradelegal-automated-grading-german-legal/)
992. **[Gradient-Guided Multi-Judge Prompt Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2026-gradient-guided-multi-judge-prompt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ChenZhuo Zhao, Xinda Wang, Pu Zhao, et al.*2026*
993. **[Graph-Based Phonetic Error Correction of Noisy ASR](https://md.research.elamur.ai/free/en/papers/singh-2026-graph-based-phonetic-error-correction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratik Rakesh Singh, Mohammadi Zaki, Aneesh Mukkamla, et al.*2026*
994. **[GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning](https://md.research.elamur.ai/free/en/papers/tian-2026-grass-gradient-based-adaptive-layer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiyuan Tian, Linbo Qiao, Yu Tang, et al.*2026*
995. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
996. [**Harm or Humor: A Multimodal, Multilingual Benchmark for Overt and Covert Harmful Humor arXiv:2603.17759**Ahmed Sharshar, Hosam Elgendy, Saad El Dine Ahmed, et al.*2026*](https://md.research.elamur.ai/free/en/papers/sharshar-2026-harm-humor-multimodal-multilingual-benchmark/)
997. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
998. **[HCMUSDroneBoys at SemEval-2026 Task 11: Asymmetric Counterfactual Debiasing and Rank-Sensitive Logical Invariance Adaptation for Syllogistic Reasoning](https://md.research.elamur.ai/free/en/papers/tran-2026-hcmusdroneboys-semeval-2026-task-11/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Nguyen Tran, Duy Minh Dao Sy, Trung Kiet Huynh, et al.*2026*
999. **[HearSay Benchmark: Do Audio LLMs Leak What They Hear?](https://md.research.elamur.ai/free/en/papers/wang-2026-hearsay-benchmark-do-audio-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Wang, Kaiwen Luo, Liang Lin, et al.*2026*
1000. [**HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language Model**Noam Kayzer, Dan Revital, Ori Bar Joseph, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kayzer-2026-hebatron-hebrew-specialized-open-weight/)

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