---
title: "Who cites Yichang Zhang — page 10 — 4,935 citing papers"
description: "4,935 papers of the Elamur Research library cite the works of Yichang Zhang, found in their bibliographies · page 10 of 15 · 901–1000; the…"
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---
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# Who cites Yichang Zhang

5,099 citations of their works from 4,935 papers of our library (of the 149,439 whose bibliographies we read) · 1,473 with a page here, the most cited first · page 10 of 15 · 901–1000 · [← Yichang Zhang](https://md.research.elamur.ai/free/en/authors/yichang-zhang/)

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901. **[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*
902. **[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*
903. **[Chinese Court Simulation with LLM-Based Agents System](https://md.research.elamur.ai/free/en/papers/zhang-2026-chinese-court-simulation-llm-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiyuan Zhang, Jiaqi Li, Yueyue Wu, et al.*2026*
904. **[Chronos: Learning Temporal Dynamics of Reasoning Chains for Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/zhang-2026-chronos-learning-temporal-dynamics-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Zhang, Jiayi Liao, Chengpeng Li, et al.*2026*
905. **[CLaC at SemEval-2026 Task 6: Response Clarity Detection in Political Discourse](https://md.research.elamur.ai/free/en/papers/turk-2026-clac-semeval-2026-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Nawar Turk, Lucas Miquet-Westphal, Leila Kosseim*2026*
906. **[CLAG: Adaptive Memory Organization via Agent-Driven Clustering for Small Language Model Agents](https://md.research.elamur.ai/free/en/papers/roh-2026-clag-adaptive-memory-organization-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taeyun Roh, WonJune Jang, Junha Jung, et al.*2026*
907. **[ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-climagent-llm-as-agents-autonomous/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Wang, Jindong Han, Wei Fan, et al.*2026*
908. **[ClinAlign: Scaling Healthcare Alignment from Clinician Preference](https://md.research.elamur.ai/free/en/papers/lyu-2026-clinalign-scaling-healthcare-alignment-clinician/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiwei Lyu, Xidong Wang, Hao Zhu, et al.*2026*
909. **[Coarse-to-Fine Multimodal Information Selection for Video Speaking Style Recognition with Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-coarse-fine-multimodal-information-selection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beibei Zhang, Yanan Lu, Lin Fen, et al.*2026*
910. **[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*
911. **[CodeRM-NT: Reward Model for Code RL without Unit Tests](https://md.research.elamur.ai/free/en/papers/xia-2026-coderm-nt-reward-model-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Xia, Dan Zhang, Tianrui Sun*2026*
912. **[CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment](https://md.research.elamur.ai/free/en/papers/shayanfar-2026-codial-interpretable-task-oriented-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Radin Shayanfar, Chu Fei Luo, Rohan V Bhambhoria, 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. **[CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering](https://md.research.elamur.ai/free/en/papers/lu-2026-cogbench-benchmarking-cognitive-alignment-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tong Lu, Zhichun Wang, Yuanhao Sun, et al.*2026*
915. **[CogNet-KG: Empowering Tutoring Dialogues with a Cognitively-Structured Knowledge Graph for STEM Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-cognet-kg-empowering-tutoring-dialogues/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ding Yu, Yu Lu, Tengju Li, et al.*2026*
916. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/zhao-2026-comet-collaborative-memory-transformer-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runsong Zhao, Shilei Liu, Jiwei Tang, et al.*2026*
917. **[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*
918. **[COMPACT: Building Compliance Paralegals via Clause Graph Reasoning over Contracts](https://md.research.elamur.ai/free/en/papers/singh-2026-compact-building-compliance-paralegals-clause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ayush Singh, Dishank Aggarwal, Pranav Bhagat, et al.*2026*
919. [**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/)
920. **[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*
921. **[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*
922. **[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*
923. **[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*
924. **[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*
925. **[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*
926. **[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*
927. **[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*
928. **[Controllable Sentence Simplification in Italian: Fine-Tuning Large Language Models on Automatically Generated Resources](https://md.research.elamur.ai/free/en/papers/papucci-2026-controllable-sentence-simplification-italian-fine/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Michele Papucci, Giulia Venturi, Felice Dell'Orletta*2026*
929. **[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*
930. **[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*
931. **[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*
932. **[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*
933. **[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*
934. **[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*
935. **[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*
936. **[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*
937. **[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*
938. **[Cultivating Forensic Reasoning for Generalizable Multimodal Manipulation Detection](https://md.research.elamur.ai/free/en/papers/zhang-2026-cultivating-forensic-reasoning-generalizable-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuchen Zhang, Yaxiong Wang, Kecheng Han, et al.*2026*
939. **[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*
940. **[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*
941. **[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*
942. **[CURUPIRA: Clever guard for harm and linguistic prompt mitigation in Brazilian Portuguese](https://md.research.elamur.ai/free/en/papers/sousa-2026-curupira-clever-guard-harm-linguistic/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Rogério Sousa, William Alberto Cruz-Castañeda, José Roberto Homeli Silva, et al.*2026*
943. **[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*
944. **[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*
945. **[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*
946. **[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*
947. **[Data-Efficient Adaptation to Contextual Shifts in LLM-based Conversational Recommendation](https://md.research.elamur.ai/free/en/papers/yang-2026-data-efficient-adaptation-contextual-shifts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hyeongjun Yang, Donghyun Kim, Seokju Hwang, et al.*2026*
948. **[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*
949. **[Deconstructing Instruction-Following: A New Benchmark for Granular Evaluation of Large Language Model Instruction Compliance Abilities](https://md.research.elamur.ai/free/en/papers/purpura-2026-deconstructing-instruction-following-new-benchmark/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alberto Purpura, Li Wang, Sahil Badyal, et al.*2026*
950. **[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*
951. **[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*
952. **[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*
953. **[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*
954. **[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*
955. **[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*
956. **[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*
957. **[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*
958. [**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/)
959. [**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/)
960. **[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*
961. **[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*
962. **[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*
963. **[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*
964. **[Disentangling Reasoning Logic to Resolve Explicit Knowledge Conflicts](https://md.research.elamur.ai/free/en/papers/zheng-2026-disentangling-reasoning-logic-resolve-explicit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianda Zheng, Zijian Huang, Meng-Fen Chiang, et al.*2026*
965. **[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*
966. **[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*
967. **[Divergent Thinking: Escape the Homogeneity Trap in Generative Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/tao-2026-divergent-thinking-escape-homogeneity-trap/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiheng Tao, Kaiwen Cheng, Zhiwei Nie, et al.*2026*
968. **[DNT at #SMM4H–HeaRD 2026: Leveraging BERT-based Encoders and LLMs for Medical Information Extraction](https://md.research.elamur.ai/free/en/papers/tien-2026-dnt-smm4h-heard-2026-leveraging/) [Social Media Mining for Health Research and Applications Workshop and Shared Tasks](https://md.research.elamur.ai/free/en/venues/smm4h/)**Doan Nhat Tien, Thìn Đặng Văn*2026*
969. **[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*
970. **[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*
971. **[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*
972. **[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*
973. **[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*
974. **[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*
975. **[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*
976. **[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*
977. **[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*
978. **[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*
979. **[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*
980. **[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*
981. **[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*
982. **[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*
983. **[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*
984. **[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*
985. **[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*
986. **[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*
987. **[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*
988. **[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*
989. [**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/)
990. [**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/)
991. **[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*
992. **[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*
993. **[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*
994. **[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*
995. **[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*
996. **[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*
997. [**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/)
998. **[Evaluating Discriminability of Vision-Language Models](https://md.research.elamur.ai/free/en/papers/muraoka-2026-evaluating-discriminability-vision-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Masayasu Muraoka, Naoaki Okazaki*2026*
999. **[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*
1000. **[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*

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