---
title: "Who cites Wenbiao Yin — page 7 — 3,360 papers of our library"
description: "3,360 papers of the Elamur Research library cite the works of Wenbiao Yin, found in their bibliographies · page 7 of 11 · 601–700; the most…"
canonical: "https://research.elamur.ai/free/en/authors/wenbiao-yin/cited-by/page/7/"
---
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# Who cites Wenbiao Yin

3,441 citations of their works from 3,360 papers of our library (of the 149,439 whose bibliographies we read) · 1,098 with a page here, the most cited first · page 7 of 11 · 601–700 · [← Wenbiao Yin](https://md.research.elamur.ai/free/en/authors/wenbiao-yin/)

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601. **[ComfyFlow: Benchmarking LLMs for AIGC Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyflow-benchmarking-llms-aigc-workflow/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Yunxin Li, et al.*2026*
602. [**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/)
603. **[COMPEL: Compensated Mixture-of-Experts Pruning with Expert-Layer distribution](https://md.research.elamur.ai/free/en/papers/yoon-2026-compel-compensated-mixture-experts-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seohee Yoon, Yong Suk Choi*2026*
604. **[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*
605. **[Concept rather than Document: Context Compression via AMR-based Conceptual Entropy](https://md.research.elamur.ai/free/en/papers/shi-2026-concept-rather-than-document-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaize Shi, Xueyao Sun, Xiaohui Tao, et al.*2026*
606. **[Confidence Leaps in LLM Reasoning: Early Stopping and Cross-Model Transfer](https://md.research.elamur.ai/free/en/papers/tikhonov-2026-confidence-leaps-llm-reasoning-early/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pavel Tikhonov, Ivan Oseledets, Elena Tutubalina*2026*
607. **[Confident, Calibrated, or Complicit: Safety Alignment and Ideological Bias in LLM Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/selvaganapathy-2026-confident-calibrated-or-complicit-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sanjeevan Selvaganapathy, Mehwish Nasim*2026*
608. **[ConMA : Confidence-Guided Kernel Sampling with Multi-Stage Aggregation for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-conma-confidence-guided-kernel-sampling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinuo Wang, Qingjie Li, Wenyao Cui, et al.*2026*
609. **[Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration](https://md.research.elamur.ai/free/en/papers/zhao-2026-consolidation-or-adaptation-prism-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Zhao, Yangou Ouyang, Xiao Ding, et al.*2026*
610. **[Context-Aware Language Understanding in Human-Robot Dialogue with LLMs](https://md.research.elamur.ai/free/en/papers/stoyanchev-2026-context-aware-language-understanding-human/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Svetlana Stoyanchev, Youmna Farag, Simon Keizer, et al.*2026*
611. **[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*
612. **[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*
613. **[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*
614. **[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*
615. **[Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language](https://md.research.elamur.ai/free/en/papers/xu-2026-creating-multilingual-mental-health-dialogue/) [Workshop on Computational Linguistics and Clinical Psychology](https://md.research.elamur.ai/free/en/venues/clpsych/)**Yunkai Xu, Saeed Abdullah*2026*
616. **[Critical-CoT: A Robust Defense Framework against Reasoning-Level Backdoor Attacks in Large Language Models](https://md.research.elamur.ai/free/en/papers/truong-2026-critical-cot-robust-defense-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vu Tuan Truong, Long Bao Le*2026*
617. **[Cross-Modal Taxonomic Generalization in (Vision-) Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-cross-modal-taxonomic-generalization-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyang Xu, Marcelo Sandoval-Castañeda, Karen Livescu, et al.*2026*
618. **[CrossDDI: Cross-Source Evidence-Grounded Drug-Drug Interaction Verification](https://md.research.elamur.ai/free/en/papers/wang-2026-crossddi-cross-source-evidence-grounded/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Hui Wang, Bohao Chu, Norbert Fuhr*2026*
619. **[CT-FineBench: A Diagnostic Fidelity Benchmark for Fine-Grained Evaluation of CT Report Generation](https://md.research.elamur.ai/free/en/papers/yuan-2026-ct-finebench-diagnostic-fidelity-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruifeng Yuan, Wanxing Chang, Weiwei Cao, et al.*2026*
620. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*
621. **[CuriosAI at SemEval-2026 Task 10:Hybrid approaches to conspiracy span extraction and conspiracy detection](https://md.research.elamur.ai/free/en/papers/takushima-2026-curiosai-semeval-2026-task-10/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Hiroki Takushima, Fumika Beppu, Aiswariya Manoj Kumar, et al.*2026*
622. **[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*
623. **[D2PCM:A Multi-Turn Dialogue Dataset with Personalized Contextual Memory](https://md.research.elamur.ai/free/en/papers/yang-2026-d2pcm-multi-turn-dialogue-dataset/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Yang, Yi Huang, Yaqin Chen, et al.*2026*
624. **[Danger Depends on the Mind: A Theory-of-Mind Grounded Dataset and Model for Context-Dependent Dangerous Speech](https://md.research.elamur.ai/free/en/papers/shi-2026-danger-depends-mind-theory-mind/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanchen Shi, Longyin Zhang, Guodong Zhou, et al.*2026*
625. **[Data Foundations of Long-Context Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/sun-2026-data-foundations-long-context-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zechen Sun, Yuyang Sun, Zhaochen Su, et al.*2026*
626. **[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*
627. **[Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say “I Don't Know”](https://md.research.elamur.ai/free/en/papers/madhwal-2026-decomposed-prompting-does-not-fix/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dhruv Madhwal, Lyuxin David Zhang, Dan Roth, et al.*2026*
628. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026*
629. **[DefGen-Bench: A Benchmark for Chinese Criminal Defence Opinion Generation in LegalAI](https://md.research.elamur.ai/free/en/papers/zhang-2026-defgen-bench-benchmark-chinese-criminal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Senbo Zhang, Qiqi Wang, Fanghao Lou, et al.*2026*
630. **[Deriving Character Logic from Storyline as Codified Decision Trees](https://md.research.elamur.ai/free/en/papers/peng-2026-deriving-character-logic-storyline-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Letian Peng, Kun Zhou, Longfei Yun, et al.*2026*
631. **[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*
632. **[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*
633. **[Detoxification for LLM: From Dataset Itself](https://md.research.elamur.ai/free/en/papers/shao-2026-detoxification-llm-dataset-itself/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Shao, Yihang Wang, Gao yu Zhu, et al.*2026*
634. **[Diagnosing LLMs via Information Spectrum Analysis: Tail Behavior and the Effects of Side Information](https://md.research.elamur.ai/free/en/papers/tachioka-2026-diagnosing-llms-information-spectrum-analysis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuuki Tachioka*2026*
635. [**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/)
636. [**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/)
637. **[DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-dica-dual-indicator-guided-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Yang, Jin Wang, Xuejie Zhang*2026*
638. **[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*
639. **[DiNO: Disinformation Narrative Observer](https://md.research.elamur.ai/free/en/papers/sosnowski-2026-dino-disinformation-narrative-observer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Witold Sosnowski, Arkadiusz Modzelewski, Kinga Skorupska, et al.*2026*
640. **[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*
641. **[Distributional Alignment for Large Language Models under Domain Shift](https://md.research.elamur.ai/free/en/papers/pham-2026-distributional-alignment-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Thanh Pham, Lizhen Qu, Zhuang Li, et al.*2026*
642. **[Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-distributional-clarity-hidden-driver-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoning Sun, Mingzhu Cai, Huang He, et al.*2026*
643. **[Do Emotions Influence Moral Judgment in Large Language Models?](https://md.research.elamur.ai/free/en/papers/saim-2026-do-emotions-influence-moral-judgment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mohammad Saim, Tianyu Jiang*2026*
644. **[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*
645. **[Do LLMs Capture Embodied Cognition and Cultural Variation? Cross-Linguistic Evidence from Demonstratives](https://md.research.elamur.ai/free/en/papers/wang-2026-do-llms-capture-embodied-cognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Wang, Emmanuele Chersoni, Chu-Ren Huang*2026*
646. **[Do We Always Need Query-Level Workflows? Rethinking Agentic Workflow Generation for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/wang-2026-do-we-always-need-query/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zixu Wang, Bingbing Xu, Yige Yuan, et al.*2026*
647. **[DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-dos-dependency-oriented-sampler-masked/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xueyu Zhou, Yangrong Hu, Jian Huang*2026*
648. **[DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-dpepo-diverse-parallel-exploration-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**JunShuo Zhang, Chengrui Huang, Feng Guo, et al.*2026*
649. **[Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving](https://md.research.elamur.ai/free/en/papers/zhang-2026-dual-cluster-memory-agent-resolving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Zhang, Yuchen Wan, Boxuan Zhang, et al.*2026*
650. **[DVMap: Fine-Grained Pluralistic Value Alignment via High-Consensus Demographic-Value Mapping](https://md.research.elamur.ai/free/en/papers/zhu-2026-dvmap-fine-grained-pluralistic-value/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengyun Zhu, Yuqi Ren, Zhen Wang, et al.*2026*
651. **[Dynamic Meta-Metrics: Source-Sentence Conditioned Weighting for MT Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-dynamic-meta-metrics-source-sentence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luke Zhang, Justin Vasselli, Aditya Khan, et al.*2026*
652. **[Dynamic Tool Dependency Retrieval for Lightweight Function Calling](https://md.research.elamur.ai/free/en/papers/patel-2026-dynamic-tool-dependency-retrieval-lightweight/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bhrij Patel, Davide Belli, Amir Jalalirad, et al.*2026*
653. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haebin Shin, Lei Ji, Xiao Liu, et al.*2026*
654. **[EA-Agent: A Structured Multi-Step Reasoning Agent for Entity Alignment](https://md.research.elamur.ai/free/en/papers/nan-2026-ea-agent-structured-multi-step/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Nan, Xixun Lin, Yanmin Shang, et al.*2026*
655. **[EduMARS: Can Vision-Language Models Grade Like Teachers? Benchmarking Multimodal, Rubric-Based Assessment on Chinese K-12 Answers](https://md.research.elamur.ai/free/en/papers/zhao-2026-edumars-can-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Zhao, Jiashun Chen, Wanting xu, et al.*2026*
656. **[Efficient Prior-Guided Reasoning for Robust Retrieval-Augmented Generation under Conflicts](https://md.research.elamur.ai/free/en/papers/yuan-2026-efficient-prior-guided-reasoning-robust/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaowei Yuan, Ziyang Huang, Zhao Yang, et al.*2026*
657. **[EfficientLLM: Unified Pruning-Aware Pretraining for Auto-Designed Compact Language Models](https://md.research.elamur.ai/free/en/papers/xing-2026-efficientllm-unified-pruning-aware-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingrun Xing, Zheng Liu, Shitao Xiao, et al.*2026*
658. **[EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME Scenarios](https://md.research.elamur.ai/free/en/papers/mu-2026-efficienttool-cost-effective-aligning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanqi Mu, Bingfeng Pi, Defei Xia, et al.*2026*
659. **[EGSS: Entropy-guided Stepwise Scaling for Reliable Software Engineering](https://md.research.elamur.ai/free/en/papers/mao-2026-egss-entropy-guided-stepwise-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenhui Mao, Yuanting Lei, Zhixiang Wei, et al.*2026*
660. **[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*
661. **[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*
662. **[EmoRes: Toward Adaptive Psychological Support via User-Agnostic Benchmark and Topic-Mining Agent](https://md.research.elamur.ai/free/en/papers/zou-2026-emores-adaptive-psychological-support-user/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengwei Zou, Xuanming Jiang, Baoyi An, et al.*2026*
663. [**Encoding Logical Relations of Chinese Complex Sentences within the Universal Dependencies Framework**Hongpu Zhu, Hongzhi Xu*2026*](https://md.research.elamur.ai/free/en/papers/zhu-2026-encoding-logical-relations-chinese-complex/)
664. [**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/)
665. **[Enhancing Lexical Relation Mining with Structured Sememe Knowledge](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-lexical-relation-mining-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hansi Wang, Qiliang Liang, Yue Wang, et al.*2026*
666. **[Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-enhancing-llm-based-search-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junzhe Wang, Zhiheng Xi, Yajie Yang, et al.*2026*
667. **[Enhancing Multilingual RAG Systems with Debiased Language Preference-Guided Query Fusion](https://md.research.elamur.ai/free/en/papers/park-2026-enhancing-multilingual-rag-systems-debiased/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jeonghyun Park, Byeongjeong Kim, Seojin Hwang, et al.*2026*
668. **[Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning](https://md.research.elamur.ai/free/en/papers/song-2026-enhancing-multimodal-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Song, Lida Shi, Ruihua Qi, et al.*2026*
669. **[Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection Prompting](https://md.research.elamur.ai/free/en/papers/yin-2026-enhancing-zero-shot-time-series/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingyou Yin, Ceyao Zhang, Min Hu, et al.*2026*
670. **[EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeom-2026-epicar-knowing-what-you-don/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jewon Yeom, Jaewon Sok, Seonghyeon Park, et al.*2026*
671. [**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/)
672. **[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*
673. **[Evaluating Memory Capability in Continuous Lifelog Scenario](https://md.research.elamur.ai/free/en/papers/zheng-2026-evaluating-memory-capability-continuous-lifelog/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianjie Zheng, Zhichen Liu, Zhanyu Shen, et al.*2026*
674. **[Evaluating Small Language Models for English-to-Portuguese Translation: Impact of Model Scale and Quantization](https://md.research.elamur.ai/free/en/papers/tamiosso-2026-evaluating-small-language-models-english/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Gustavo Lopes Tamiosso, Rafael Oleques Nunes, Dennis Giovani Balreira*2026*
675. **[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*
676. **[Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for Classification](https://md.research.elamur.ai/free/en/papers/merdjanovska-2026-evaluation-pitfalls-sparsity-limitations-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elena Merdjanovska, Omar Zaidan, Andreas Rücklé*2026*
677. **[Everyone is unique: Towards Behaviorally Heterogeneous Negotiation Dialogue Systems for Debt Collection](https://md.research.elamur.ai/free/en/papers/yang-2026-everyone-is-unique-behaviorally-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Yang, Kai Tang, Chao Ye, et al.*2026*
678. **[EVGeoQA: Benchmarking LLMs on Dynamic, Multi-Objective Geo-Spatial Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-evgeoqa-benchmarking-llms-dynamic-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianfei Wu, Zhichun Wang, Zhensheng Wang, et al.*2026*
679. **[Evo-Attacker: Memory-Augmented Reinforcement Learning for Long-Horizon Tool Attacks on LLM-MAS](https://md.research.elamur.ai/free/en/papers/yan-2026-evo-attacker-memory-augmented-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bingyu Yan, Xiaoming Zhang, JinYu Hou, et al.*2026*
680. **[EvoMD-LLM: Learning the Language of Species Evolution in Reactive Molecular Dynamics](https://md.research.elamur.ai/free/en/papers/tang-2026-evomd-llm-learning-language-species/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichen Tang, Zhengzheng Dang, Yulin Chen, et al.*2026*
681. **[EvoMemKG: An Evolvable Memory Agent for Multi-hop Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tian-2026-evomemkg-evolvable-memory-agent-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiyu Tian, Shuyue Xing, Zhuoxin Han, et al.*2026*
682. **[Experience is the Teacher: Reusing Atomic Thoughts from LLMs to Improve Medical Dialogue](https://md.research.elamur.ai/free/en/papers/yu-2026-experience-is-teacher-reusing-atomic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangya Yu, Hui Luo, Qi Ye, et al.*2026*
683. **[Exploiting Tree Structure for Credit Assignment in Reinforcement Learning with Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2026-exploiting-tree-structure-credit-assignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hieu Tran, Zonghai Yao, Hong yu*2026*
684. **[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*
685. **[Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck](https://md.research.elamur.ai/free/en/papers/zhang-2026-failure-modes-multi-hop-qa/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meiru Zhang, Zaiqiao Meng, Nigel Collier*2026*
686. **[FalconCopilot: Empowering LLMs Towards Integrated Human-Machine Systems for Aviation Autonomy](https://md.research.elamur.ai/free/en/papers/yan-2026-falconcopilot-empowering-llms-integrated-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyuan Yan, Qingchen Liu, Qichao Ma, et al.*2026*
687. **[FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments](https://md.research.elamur.ai/free/en/papers/saeidi-2026-fama-failure-aware-meta-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amir Saeidi, Venkatesh Mishra, Souradeep Mukhopadhyay, et al.*2026*
688. **[Far Out: Evaluating Language Models on Slang in Australian and Indian English](https://md.research.elamur.ai/free/en/papers/dilsiz-2026-far-out-evaluating-language-models/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Deniz Kaya Dilsiz, Dipankar Srirag, Aditya Joshi*2026*
689. **[Field of Science and Technology Classification of Academic Documents in Portuguese](https://md.research.elamur.ai/free/en/papers/simoes-2026-field-science-technology-classification-academic/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Ivo Simões, Hugo Gonçalo Oliveira, João Correia*2026*
690. [**Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning arXiv:2608.18361**Mena Attia, Mona Diab, Thamar Solorio*2026*](https://md.research.elamur.ai/free/en/papers/attia-2026-figurative-cultural-knowledge-llms-investigating/)
691. **[Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management](https://md.research.elamur.ai/free/en/papers/ma-2026-fine-mem-fine-grained-feedback/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weitao Ma, Xiaocheng Feng, Lei Huang, et al.*2026*
692. **[Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas](https://md.research.elamur.ai/free/en/papers/stahelin-2026-fine-tuning-hierarchical-prompting-robust/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lukas Stähelin, Veronika Solopova, Max Upravitelev, et al.*2026*
693. **[Fisher-Driven Adaptive Locating for Knowledge Editing in Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-fisher-driven-adaptive-locating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenghao Xu, Jiexi Yan, Guangtao Lyu, et al.*2026*
694. **[FMISUYotkovaKastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals](https://md.research.elamur.ai/free/en/papers/yotkova-2026-fmisuyotkovakastreva-semeval-2026-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Elitsa Yotkova, Violeta Kastreva, Dimitar Dimitrov, et al.*2026*
695. **[FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean](https://md.research.elamur.ai/free/en/papers/meadows-2026-formalscience-scalable-human-loop-autoformalisation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jordan Meadows, Lan Zhang, Andre Freitas*2026*
696. **[Format-Adapter: Improving Reasoning Capability of LLMs by Adapting Suitable Format](https://md.research.elamur.ai/free/en/papers/wang-2026-format-adapter-improving-reasoning-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dingzirui Wang, Xuanliang Zhang, Rongyu Cao, et al.*2026*
697. **[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*
698. **[From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation Tasks](https://md.research.elamur.ai/free/en/papers/ren-2026-coarse-fine-benchmarking-reward-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Ren, Tianjun Pan, Xingzhou Chen, et al.*2026*
699. **[From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents](https://md.research.elamur.ai/free/en/papers/tan-2026-coarse-fine-self-adaptive-hierarchical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Tan, Zeyu Zhang, Chen Ma, et al.*2026*
700. **[From Conversation to Evaluation: Benchmarking LLMs on Development Knowledge via SimpleDevQA](https://md.research.elamur.ai/free/en/papers/zhang-2026-conversation-evaluation-benchmarking-llms-development/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Zhang, Lianghong Guo, Yanlin Wang, et al.*2026*

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