---
title: "Who cites Carissa Schoenick — page 5 — 2,111 citing papers"
description: "2,111 papers of the Elamur Research library cite the works of Carissa Schoenick, found in their bibliographies · page 5 of 6 · 401–500; the…"
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---
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# Who cites Carissa Schoenick

2,131 citations of their works from 2,111 papers of our library (of the 149,439 whose bibliographies we read) · 532 with a page here, the most cited first · page 5 of 6 · 401–500 · [← Carissa Schoenick](https://md.research.elamur.ai/free/en/authors/carissa-schoenick/)

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401. **[Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2026-diffuse-thinking-exploring-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenyang Shao, Sijian Ren, Fengli Xu, et al.*2026 · 1 citation*
402. **[Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration](https://md.research.elamur.ai/free/en/papers/zhong-2026-efficient-self-evaluation-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linhao Zhong, Linyu Wu, Wen Wang, et al.*2026 · 1 citation*
403. **[Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-enhancing-linguistic-competence-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atsuki Yamaguchi, Maggie Mi, Nikolaos Aletras*2026 · 1 citation*
404. **[From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan](https://md.research.elamur.ai/free/en/papers/yang-2026-curated-data-scalable-models-continual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Yang, Leiyu Pan, Bojian Xiong, et al.*2026 · 1 citation*
405. **[From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-local-global-revisiting-structured-pruning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyan Wang, Enmao Diao, Qi Le, et al.*2026 · 1 citation*
406. **[InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling](https://md.research.elamur.ai/free/en/papers/shi-2026-inferencedynamics-adaptive-llm-routing-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Shi, Tianshi Zheng, Weiqi Wang, et al.*2026 · 1 citation*
407. **[Iterative Structured Pruning for Large Language Models with Multi-Domain Calibration](https://md.research.elamur.ai/free/en/papers/wu-2026-iterative-structured-pruning-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Guangxin Wu, Hao Zhang, Zhang Zhibin, et al.*2026 · 1 citation*
408. **[KDW at SemEval-2026 Task 12: Logic-Driven Distillation with Knowledge Graphs for Efficient Abductive Reasoning](https://md.research.elamur.ai/free/en/papers/zhu-2026-kdw-semeval-2026-task-12/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Sihan Zhu, Hongjie Wu, Xinyan Xu*2026 · 1 citation*
409. [**KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full Report arXiv:2606.03773**Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kraus-2026-klettermix-climbing-toward-high-quality/)
410. **[Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions](https://md.research.elamur.ai/free/en/papers/zhang-2026-polynomial-expansion-rank-adaptation-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Zhang, Lin Mu, Li Ni, et al.*2026 · 1 citation*
411. **[Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets](https://md.research.elamur.ai/free/en/papers/yukhymenko-2026-recovered-translation-efficient-pipeline-automated/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanna Yukhymenko, Anton Alexandrov, Martin Vechev*2026 · 1 citation*
412. **[RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering](https://md.research.elamur.ai/free/en/papers/ye-2026-riser-orchestrating-latent-reasoning-skills/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wencheng Ye, Xiaoyang Yuan, Yi Bin, et al.*2026 · 1 citation*
413. **[RotBench: Evaluating Multi-modal Large Language Models on Identifying Image Rotation](https://md.research.elamur.ai/free/en/papers/niu-2026-rotbench-evaluating-multi-modal-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, et al.*2026 · 1 citation*
414. **[SharVeT: Similarity-aware Parameter Sharing with Vector-based Tuning for Efficient LLM Compression](https://md.research.elamur.ai/free/en/papers/yun-2026-sharvet-similarity-aware-parameter-sharing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeongin Yun, Jaeri Lee, Jongjin Kim, et al.*2026 · 1 citation*
415. **[TELL-TALE: Task Efficient LLMs with Task Aware Layer Elimination](https://md.research.elamur.ai/free/en/papers/naim-2026-tell-tale-task-efficient-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Naim, Krish Sharma, Niyar R Barman, et al.*2026 · 1 citation*
416. **[The Role of Mixed-Language Documents for Multilingual Large Language Model Pretraining](https://md.research.elamur.ai/free/en/papers/shao-2026-role-mixed-language-documents-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiandong Shao, Raphael Tang, Crystina Zhang, et al.*2026 · 1 citation*
417. **[ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding](https://md.research.elamur.ai/free/en/papers/song-2026-thinkbrake-efficient-reasoning-log-probability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sangjun Song, Minjae Oh, Seungkyu Lee, et al.*2026 · 1 citation*
418. **[Unleashing Low-Bit Inference on Ascend NPUs: A Comprehensive Evaluation of HiFloat Formats](https://md.research.elamur.ai/free/en/papers/zhao-2026-unleashing-low-bit-inference-ascend/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengxiang Zhao, Hui-Ling Zhen, Xing Li, et al.*2026 · 1 citation*
419. **[VecCISC: Improving Confidence-Informed Self-Consistency with Reasoning Trace Clustering and Candidate Answer Selection](https://md.research.elamur.ai/free/en/papers/petullo-2026-veccisc-improving-confidence-informed-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**James Petullo, Sonny George, Dylan Cashman, et al.*2026 · 1 citation*
420. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
421. [**Mix, MinHash, and Match: Cross-Source Agreement for Multilingual Pretraining Datasets arXiv:2512.18834**Sultan Alrashed, Francesco Orabona*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alrashed-2025-mix-minhash-match-cross-source/)
422. [**Aquila2 Technical Report arXiv:2408.07410**Bo-Wen Zhang, Liangdong Wang, Jijie Li, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aquila2-technical-report/)
423. **[Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-dreaming-out-loud-self-synthesis/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Badr AlKhamissi, Yingtian Tang, Abdülkadir Gökce, et al.*2024 · 1 citation*
424. **[QA-KGNet: Language Model-driven Knowledge Graph Question-answering Model (QA-KGNet: 一种语言模型驱动的知识图谱问答模型)](https://md.research.elamur.ai/free/en/papers/qiao-2023-qa-kgnet-language/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Shaojie Qiao (乔少杰), Guoping Yang (杨国平), Yong Yu (于泳), et al.*2023 · 1 citation*
425. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
426. **[ACBQ: Adaptive Cross-Block Quantization of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-acbq-adaptive-cross-block-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hailing Wang, Jianglin Lu, Yitian Zhang, et al.*2026*
427. **[Activation Decomposition and Steering for LLM Backdoor Remediation](https://md.research.elamur.ai/free/en/papers/zhong-2026-activation-decomposition-steering-llm-backdoor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingfeng Zhong, Qiongkai Xu, Usman Naseem*2026*
428. **[Adapting Vision-Language Models for E-commerce Understanding at Scale](https://md.research.elamur.ai/free/en/papers/nulli-2026-adapting-vision-language-models-e/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Matteo Nulli, Vladimir Orshulevich, Tala Bazazo, et al.*2026*
429. **[Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards](https://md.research.elamur.ai/free/en/papers/xie-2026-advancing-reasoning-diffusion-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoan Xie, Lingjing Kong, Xiangchen Song, et al.*2026*
430. **[Agentic Oversight via Dialectic Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2026-agentic-oversight-dialectic-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Federico Ranaldi*2026*
431. **[AMATA: Adaptive Multi-Agent Trajectory Alignment for Knowledge-Intensive Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2026-amata-adaptive-multi-agent-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taolin Zhang, Dongyang Li, Chen Chen, et al.*2026*
432. **[An Evaluation of Classifiers for Mapping Generative LLM Responses to Answer Options of Multiple-choice Questionnaires](https://md.research.elamur.ai/free/en/papers/stroligo-2026-evaluation-classifiers-mapping-generative-llm/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alisea Stroligo, Anna Shamray, Julian Schelb, et al.*2026*
433. **[Attention Under Attack: Analog Noise Effects and Mechanistic Vulnerabilities in Transformer Models](https://md.research.elamur.ai/free/en/papers/rahman-2026-attention-under-attack-analog-noise/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mafizur Rahman, Lijun Qian*2026*
434. **[Balancing Knowledge Breadth and Task Depth for Effective Domain Adaptation Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-balancing-knowledge-breadth-task-depth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mu Zhang, Yuxiang Chu, Guangya Yu, et al.*2026*
435. **[Bears, all bears, and some bears. Language Constraints on Language Models' Inductive Inferences](https://md.research.elamur.ai/free/en/papers/padmanabhan-2026-bears-all-bears-some-bears/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sriram Padmanabhan, Siyuan Song, Kanishka Misra*2026*
436. **[Benchmarking Post-Training Quantization of Large Language Models under Microscaling Floating Point Formats](https://md.research.elamur.ai/free/en/papers/zhang-2026-benchmarking-post-training-quantization-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Manyi Zhang, Ji-Fu Li, Zhongao Sun, et al.*2026*
437. **[Beyond Uniform SVD: Dual-Level Optimization across Columns and Modules for LLM Compression](https://md.research.elamur.ai/free/en/papers/xv-2026-beyond-uniform-svd-dual-level/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Xv, Xian Gao, Ting Liu, et al.*2026*
438. **[Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level Annotation](https://md.research.elamur.ai/free/en/papers/touchent-2026-biomed-enriched-data-efficient-biomedical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rian Touchent, Nathan Godey, Éric Villemonte de la Clergerie*2026*
439. **[BWLA: Breaking the Barrier of W1AX Post-Training Quantization for LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-bwla-breaking-barrier-w1ax-post/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhixiong Zhao, Zukang Xu, Dawei Yang*2026*
440. **[Charting the European LLM Benchmarking Landscape: A New Taxonomy and Registry](https://md.research.elamur.ai/free/en/papers/vintar-2026-charting-european-llm-benchmarking-landscape/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Spela Vintar, Mojca Brglez, Taja Kuzman Pungeršek, et al.*2026*
441. **[Common Objects Out of Context (COOCo): Investigating Multimodal Context and Semantic Scene Violations in Referential Communication](https://md.research.elamur.ai/free/en/papers/merlo-2026-common-objects-out-context-cooco/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Filippo Merlo, Ece Takmaz, Wenkai Chen, et al.*2026*
442. **[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*
443. **[Component Transfer Can Exceed Full Model Performance: Investigating Post-Trained Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/tiwari-2026-component-transfer-can-exceed-full/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Rabin Tiwari*2026*
444. **[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*
445. **[Controllable Contamination Detection for Reliable LLM Evaluation with Statistical Guarantees](https://md.research.elamur.ai/free/en/papers/zhang-2026-controllable-contamination-detection-reliable-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Zhang, Qi Liu, Siyuan Liang, et al.*2026*
446. **[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*
447. **[CSULoRA: Closest Safe Update Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/marchenko-2026-csulora-closest-safe-update-low/) [International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security](https://md.research.elamur.ai/free/en/venues/nlpaics/)**Oleksandr Marchenko, Adelaide Danilov, Aria Nourbakhsh, et al.*2026*
448. **[Decoupling Generalization and Adaptation in Meta-Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/vetcha-2026-decoupling-generalization-adaptation-meta-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitin Vetcha, Binqian Xu, Dianbo Liu*2026*
449. **[Demystifying Mixed Outcomes of Self-Training: Pre-training Analyses on Non-Toy LLMs](https://md.research.elamur.ai/free/en/papers/nakamura-2026-demystifying-mixed-outcomes-self-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yusuke Nakamura, Hirokazu Kiyomaru, Chaoran Liu, et al.*2026*
450. **[Diagnosing Translated Benchmarks: An Automated Quality Assurance Study of the EU20 Benchmark Suite](https://md.research.elamur.ai/free/en/papers/thellmann-2026-diagnosing-translated-benchmarks-automated-quality/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Klaudia Thellmann, Bernhard Stadler, Michael Färber*2026*
451. **[Disentangling the Effects of Unlearning in Measuring Parametric Faithfulness of Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/mitsuhashi-2026-disentangling-effects-unlearning-measuring-parametric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ryo Mitsuhashi, Gaku Morio, Ayana Niwa, et al.*2026*
452. **[Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-tell-answer-truly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyi Wang, Jinyi Han, Zishang Jiang, et al.*2026*
453. **[Dual Activation-Weight Sparsity: A Training-Free Framework for Efficient Large Language Model Compression](https://md.research.elamur.ai/free/en/papers/sun-2026-dual-activation-weight-sparsity-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luoyang Sun, Guangyan Li, Cheng Deng, et al.*2026*
454. **[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*
455. **[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*
456. **[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*
457. **[FAQ: Mitigating Quantization Error via Regenerating Calibration Data with Family-Aware Quantization](https://md.research.elamur.ai/free/en/papers/xiao-2026-faq-mitigating-quantization-error-regenerating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Xiao, Weiqing Li, Jinyue Guo, et al.*2026*
458. **[G-LoRA: Global-Local Decoupled Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/xiong-2026-g-lora-global-local-decoupled/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiahao Xiong, Yihong Huang, Yihe Liu, et al.*2026*
459. **[GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer Selection](https://md.research.elamur.ai/free/en/papers/yao-2026-gast-gradient-aligned-sparse-tuning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kai Yao, Zhenghan Song, Kaixin Wu, et al.*2026*
460. **[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*
461. **[GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-grace-generative-approach-better-confidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2026*
462. **[GRASPrune: Global Gating for Budgeted Structured Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-grasprune-global-gating-budgeted-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyang Wang, Jiangfeng Xiao, Chuan Xiao, et al.*2026*
463. **[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*
464. **[Grounded Concreteness: Human-Like Concreteness Sensitivity in Vision–Language Models](https://md.research.elamur.ai/free/en/papers/roy-2026-grounded-concreteness-human-like-concreteness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Aryan Roy, Zekun Wang, Christopher J. MacLellan*2026*
465. [**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/)
466. **[How Can Synthetic Data Improve Multilingual Language Model Pretraining? A Data Quality Perspective](https://md.research.elamur.ai/free/en/papers/zhu-2026-how-can-synthetic-data-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongyao Zhu, Qian Liu, Chang Ma, et al.*2026*
467. **[How effective are VLMs in assisting humans in inferring the quality of mental models from Multimodal short answers?](https://md.research.elamur.ai/free/en/papers/sil-2026-how-effective-are-vlms-assisting/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pritam Sil, Durgaprasad Karnam, Vinay Reddy Venumuddala, et al.*2026*
468. **[ImF: Embedding an Implicit Fingerprint in Your Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-imf-embedding-implicit-fingerprint-your/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wu, Wanli Peng, Hang fu, et al.*2026*
469. **[Interpretable Safety Alignment via SAE-Constructed Low-Rank Subspace Adaptation](https://md.research.elamur.ai/free/en/papers/wang-2026-interpretable-safety-alignment-sae-constructed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dianyun Wang, Qingsen Ma, Yuhu Shang, et al.*2026*
470. **[JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-judgeagent-beyond-static-benchmarks-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Shi, Xuhui Jiang, Chengjin Xu, et al.*2026*
471. **[KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-knowledgeberg-evaluating-systematic-knowledge-coverage/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Zhang, Qianru Meng, Yongjian Chen, et al.*2026*
472. **[LaCo: Layer-wise Compensation for Pruned Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-laco-layer-wise-compensation-pruned/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yingen Liu, Fan Wu, Panxuyan, et al.*2026*
473. **[LaCoMSA: Language-Consistency Multilingual Self-Alignment with Latent Representation Rewarding](https://md.research.elamur.ai/free/en/papers/tran-2026-lacomsa-language-consistency-multilingual-self/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Khanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen*2026*
474. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuemiao Zhang, Chengying Tu, Can Ren, et al.*2026*
475. **[Layer-Wise High-Impact Parameter Ratio Optimization in Post-Training Quantization for Large Language Models](https://md.research.elamur.ai/free/en/papers/pham-2026-layer-wise-high-impact-parameter/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cuong Pham, Anh Dung Hoang, Cuong C. Nguyen, et al.*2026*
476. **[LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation](https://md.research.elamur.ai/free/en/papers/song-2026-lbllm-lightweight-binarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siqing Song, Chuang Wang, Yong Lang, et al.*2026*
477. **[LeLoRA: Learnable Low-Rank Adaptation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lelora-learnable-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, et al.*2026*
478. **[LEPO: Latent Reasoning Policy Optimization for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lepo-latent-reasoning-policy-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyan Zhou, Jiarui Yu, Hande Dong, et al.*2026*
479. **[Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States](https://md.research.elamur.ai/free/en/papers/sahoo-2026-linear-probes-detect-task-format/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Subramanyam Sahoo, Vinija Jain, Aman Chadha, et al.*2026*
480. **[LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points](https://md.research.elamur.ai/free/en/papers/zhang-2026-linkqa-synthesizing-diverse-qa-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuemiao Zhang, Can Ren, Chengying Tu, et al.*2026*
481. **[LLEOT: A Privacy-Enhancing Offsite Tuning Framework via Loss Landscape Elevation](https://md.research.elamur.ai/free/en/papers/zhong-2026-lleot-privacy-enhancing-offsite-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jin Zhong, Jinglin Liang, Tongtong Yang, et al.*2026*
482. **[Localized Low-Rank Adaptation within Clustered Parameter Subspaces](https://md.research.elamur.ai/free/en/papers/xiong-2026-localized-low-rank-adaptation-within/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahao Xiong, Yihe Liu, Xianming Hu, et al.*2026*
483. **[Map-of-Actions: Deliberate Reasoning over Multi-Labeled Graphs](https://md.research.elamur.ai/free/en/papers/ni-2026-map-actions-deliberate-reasoning-over/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Wuguang Ni, Kai Yang*2026*
484. **[MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/xiao-2026-mass-rag-multi-agent-synthesis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingchen Xiao, Heyan Huang, Runheng Liu, et al.*2026*
485. **[MDP-GRPO: Stabilized Group Relative Policy Optimization for Multi-Constraint Instruction Following](https://md.research.elamur.ai/free/en/papers/zarchi-2026-mdp-grpo-stabilized-group-relative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Mahdi Salmani-Zarchi, Zahra Rahimi, Heshaam Faili, et al.*2026*
486. **[Memory Dial: A Training Framework for Controllable Memorization in Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-memory-dial-training-framework-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangbo Zhang, Ali Emami*2026*
487. **[Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO](https://md.research.elamur.ai/free/en/papers/zheng-2026-mitigating-selection-bias-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinquan Zheng, Jia Yuan, Jiacheng Yao, et al.*2026*
488. **[ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource Settings](https://md.research.elamur.ai/free/en/papers/liu-2026-modularmoe-fast-llm-customization-parameter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxing Liu, Qi Qi, Haifeng Sun, et al.*2026*
489. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*
490. **[Offline Preference Optimization via Maximum Marginal Likelihood Estimation](https://md.research.elamur.ai/free/en/papers/najafi-2026-offline-preference-optimization-maximum-marginal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Saeed Najafi, Alona Fyshe*2026*
491. **[On the Editability of Delta Parameters in Post-Trained Models](https://md.research.elamur.ai/free/en/papers/tang-2026-editability-delta-parameters-post-trained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiaoyu Tang, Le Yu, Bowen Yu, et al.*2026*
492. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
493. **[PE-QAT: Parameter-Efficient Quantization-Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/mishra-2026-pe-qat-parameter-efficient-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shresth Mishra*2026*
494. **[Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers](https://md.research.elamur.ai/free/en/papers/shimizu-2026-position-encoding-random-float-sampling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Atsushi Shimizu, Shohei Taniguchi, Yutaka Matsuo*2026*
495. **[Profiling-Free Mixed-Precision Quantization for MoE LLMs via Fuzzy Rule Interpolation](https://md.research.elamur.ai/free/en/papers/qi-2026-profiling-free-mixed-precision-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huachen Qi, Ruiyu Zhuo, Bowen Shi, et al.*2026*
496. **[RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation](https://md.research.elamur.ai/free/en/papers/xu-2026-rag-wild-effectiveness-llms-mixture/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ran Xu, Yuchen Zhuang, Yue Yu, et al.*2026*
497. **[RanLoRA: Residual-aware Nonlinear Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/luo-2026-ranlora-residual-aware-nonlinear-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Luo, Yongbin Liu, Chunping Ouyang, et al.*2026*
498. **[ReasonAny: Incorporating Reasoning Capability to Any Model via Simple and Effective Model Merging](https://md.research.elamur.ai/free/en/papers/yang-2026-reasonany-incorporating-reasoning-capability-any/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyao Yang, Chen Qian, Wen Shen, et al.*2026*
499. **[Rethinking Data Mixing from the Perspective of Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-rethinking-data-mixing-perspective-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanjian Xu, Tianze Sun, Changwei Xu, et al.*2026*
500. **[River-LLM: Large Language Model Seamless Exit Based on KV Share](https://md.research.elamur.ai/free/en/papers/shen-2026-river-llm-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yingtao Shen, An Zou*2026*

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