---
title: "Who cites Thomas Icard — page 5 — 2,020 papers of our library"
description: "2020 papers of the Elamur Research library cite the works of Thomas Icard, found in their bibliographies · page 5 of 5 · 401–494; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/thomas-icard/cited-by/page/5/"
---
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# Who cites Thomas Icard

2,296 citations of their works from 2,020 papers of our library (of the 149,439 whose bibliographies we read) · 494 with a page here, the most cited first · page 5 of 5 · 401–494 · [← Thomas Icard](https://md.research.elamur.ai/free/en/authors/thomas-icard/)

[← prev](https://md.research.elamur.ai/free/en/authors/thomas-icard/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/thomas-icard/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/thomas-icard/cited-by/page/4/) **5**

401. **[Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?](https://md.research.elamur.ai/free/en/papers/xin-2026-jailbreaking-attacks-vs-content-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xin, Dingfan Chen, Linyi Yang, et al.*2026 · 3 citations*
402. **[Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2026-sparse-brains-are-also-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiheng Yang, Yujie Wang, Chi Ma, et al.*2026 · 3 citations*
403. **[Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs Against English Varieties](https://md.research.elamur.ai/free/en/papers/lee-2025-trans-env-framework-evaluating-linguistic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiyoung Lee, Seungho Kim, Jieun Han, et al.*2025 · 3 citations*
404. **[Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization](https://md.research.elamur.ai/free/en/papers/xing-2026-are-llms-reliable-rankers-rank/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Xing, Jerry Li, Yixuan Du, et al.*2026 · 2 citations*
405. **[Benchmarking Large Language Models for Chinese and Japanese IMEs: Phonetic-to-Character Generation and Textual Error Correction](https://md.research.elamur.ai/free/en/papers/zou-2026-benchmarking-large-language-models-chinese/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuchun Zou, Tedd Lee, Xiaodi Fan, et al.*2026 · 2 citations*
406. **[Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation](https://md.research.elamur.ai/free/en/papers/shen-2026-preconditioned-test-time-adaptation-out/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanwen Shen, Ting Ying, Jiajie Lu, et al.*2026 · 2 citations*
407. [**WASIL: In-the-Wild Arabic Spoken Interactions with LLMs arXiv:2605.16364**Zien Sheikh Ali, Hamdy Mubarak, Soon-Gyo Jung, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ali-2026-wasil-wild-arabic-spoken-interactions/)
408. **[On Quick Kisses and How to Make Them Count: A Study on Event Construal in Light Verb Constructions with BERT](https://md.research.elamur.ai/free/en/papers/liu-2023-quick-kisses-how-make-them/) [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/)**Chenxin Liu, Emmanuele Chersoni*2023 · 2 citations*
409. **[Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models](https://md.research.elamur.ai/free/en/papers/li-2023-pragmatic-reasoning-unlocks-quantifier-semantics/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yiyuan Li, Rakesh Menon, Sayan Ghosh, et al.*2023 · 2 citations*
410. **[AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agenticeval-agentic-self-evolving-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixu Wang, Xin Wang, Yang Yao, et al.*2026 · 1 citation*
411. **[Aligned Probing: Relating Toxic Behavior and Model Internals](https://md.research.elamur.ai/free/en/papers/waldis-2026-aligned-probing-relating-toxic-behavior/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Andreas Waldis, Vagrant Gautam, Anne Lauscher, et al.*2026 · 1 citation*
412. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
413. **[Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists](https://md.research.elamur.ai/free/en/papers/pietruszka-2026-can-models-help-us-create/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michał Pietruszka, Łukasz Borchmann, Aleksander Jędrosz, et al.*2026 · 1 citation*
414. **[Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors](https://md.research.elamur.ai/free/en/papers/yin-2026-compiling-activation-steering-into-weights/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Yin, Tianxu Han, Naen Xu, et al.*2026 · 1 citation*
415. **[Constructing Interpretable Features from Compositional Neuron Groups](https://md.research.elamur.ai/free/en/papers/shafran-2026-constructing-interpretable-features-compositional-neuron/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or David Shafran, Atticus Geiger, Mor Geva*2026 · 1 citation*
416. **[Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models](https://md.research.elamur.ai/free/en/papers/yin-2026-decentralized-arena-democratic-scalable-automatic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanbin Yin, Kun Zhou, Zhen Wang, et al.*2026 · 1 citation*
417. **[Deciphering Cultural Representations in Large Language Models via Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zou-2026-deciphering-cultural-representations-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenye Zou, Difan Jiao, Lijie Hu*2026 · 1 citation*
418. **[Evaluating Linguistic Knowledge of LLMs in Tamil: The ILAKKANAM Benchmark](https://md.research.elamur.ai/free/en/papers/varsha-2026-evaluating-linguistic-knowledge-llms-tamil/) [workshop on Challenges in Processing South Asian Languages](https://md.research.elamur.ai/free/en/venues/chipsal/)**Jeyarajalingam Varsha, Menan Velayuthan, Sumirtha Karunakaran, et al.*2026 · 1 citation*
419. **[From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-passive-metric-active-signal-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxin Zhang, Wendi Cui, Zhuohang Li, et al.*2026 · 1 citation*
420. **[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://md.research.elamur.ai/free/en/papers/ostermann-2026-weights-activations-is-steering-next/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, et al.*2026 · 1 citation*
421. **[From “Thinking” to “Justifying”: Aligning High-Stakes Explainability with Professional Communication Standards](https://md.research.elamur.ai/free/en/papers/qian-2026-thinking-justifying-aligning-high-stakes/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Qian, Yimeng Wang, Yu Chen, et al.*2026 · 1 citation*
422. **[Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/song-2026-mechanistic-interpretability-should-prioritize-feature/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchen Song, Aashiq Muhamed, Yujia Zheng, et al.*2026 · 1 citation*
423. **[Multi-component Causal Tracing in Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-multi-component-causal-tracing-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zirui Yan, Dennis Wei, Dmitriy A Katz, et al.*2026 · 1 citation*
424. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
425. **[ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting](https://md.research.elamur.ai/free/en/papers/tian-2026-reattn-improving-attention-based-re/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxing Tian, Fengran Mo, Weixu Zhang, et al.*2026 · 1 citation*
426. **[Rethinking Scale: Deployment Trade-offs of Small Language Models under Agent Paradigms](https://md.research.elamur.ai/free/en/papers/wang-2026-rethinking-scale-deployment-trade-offs/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinlin Wang*2026 · 1 citation*
427. **[Start Making Sense(s): A Developmental Probe of Attention Specialization Using Lexical Ambiguity](https://md.research.elamur.ai/free/en/papers/riviere-2026-start-making-sense-s-developmental/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pamela D. Rivière, Sean Trott*2026 · 1 citation*
428. **[The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMs](https://md.research.elamur.ai/free/en/papers/tahan-2026-mighty-torr-benchmark-table-reasoning/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Shir Ashury-Tahan, Yifan Mai, Rajmohan C, et al.*2026 · 1 citation*
429. **[User Perceptions vs. Proxy LLM Judges: Privacy and Helpfulness in LLM Responses to Privacy-Sensitive Scenarios](https://md.research.elamur.ai/free/en/papers/wu-2026-user-perceptions-vs-proxy-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Wu, Roshni Kaushik, Wenkai Li, et al.*2026 · 1 citation*
430. [**Learning from Convenience Samples: A Case Study on Fine-Tuning LLMs for Survey Non-response in the German Longitudinal Election Study arXiv:2509.25063**Tobias Holtdirk, Dennis Assenmacher, Arnim Bleier, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/holtdirk-2025-learning-convenience-samples-case-study/)
431. [**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/)
432. [**Language Models are Bounded Pragmatic Speakers: Understanding RLHF from a Bayesian Cognitive Modeling Perspective arXiv:2305.17760**Khanh Nguyen*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-language-models-bounded-pragmatic-speakers/)
433. **[A framework for analyzing concept representations in neural models](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Burin Naowarat, Hao Tang, Sharon Goldwater*2026*
434. **[AAPO: Enhancing the Reasoning Capabilities of LLMs with Advantage Margin](https://md.research.elamur.ai/free/en/papers/xiong-2026-aapo-enhancing-reasoning-capabilities-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jian Xiong, Jingbo Zhou, Jingyong Ye, et al.*2026*
435. **[Accelerating LLM Fine-Tuning via Embedding Knowledge Transfer](https://md.research.elamur.ai/free/en/papers/peng-2026-accelerating-llm-fine-tuning-embedding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meishu Peng, Ziyue Zhang, Yi Zhang, et al.*2026*
436. **[Actionable Interpretability for Churn Classification: A Text Bottleneck Model Case Study at a Major Telecom Provider](https://md.research.elamur.ai/free/en/papers/sauter-2026-actionable-interpretability-churn-classification-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adrian Sauter, Vera Neplenbroek, Georgios Vlassopoulos, et al.*2026*
437. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong She, Xianrong Yao, Liqun Chen, et al.*2026*
438. **[AmazoniaNLP: A Survey of Extreme Low-Resource Languages in the Peruvian-Brazilian Amazon](https://md.research.elamur.ai/free/en/papers/zevallos-2026-amazonianlp-survey-extreme-low-resource/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Rodolfo Joel Zevallos, Fabrício Carraro, John E. Ortega*2026*
439. [**ArabicNumBench: Evaluating Arabic Number Reading in Large Language Models arXiv:2602.18776**Anas Alhumud, Abdulaziz Alhammadi, Muhammad Badruddin Khan*2026*](https://md.research.elamur.ai/free/en/papers/alhumud-2026-arabicnumbench-evaluating-arabic-number-reading/)
440. **[Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers](https://md.research.elamur.ai/free/en/papers/zhao-2026-are-my-optimized-prompts-compromised/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.*2026*
441. **[Automatic Paper Analysis and Categorisation for Systematic Reviews with Combined Reasoning-Augmented SFT and DAPO RL](https://md.research.elamur.ai/free/en/papers/lorandi-2026-automatic-paper-analysis-categorisation-systematic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michela Lorandi, Anya Belz, Simon Mille, et al.*2026*
442. **[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*
443. **[Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026*
444. **[BenchNavigator: A Discovery Interface for Comparing LLM Benchmarks](https://md.research.elamur.ai/free/en/papers/sokol-2026-benchnavigator-discovery-interface-comparing-llm/) [Workshop on Evaluating Evaluations (EvalEval)](https://md.research.elamur.ai/free/en/venues/evaleval/)**Anna Sokol, Inge Vejsbjerg, Elizabeth M. Daly, et al.*2026*
445. **[Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs](https://md.research.elamur.ai/free/en/papers/williams-2026-beyond-marginal-distributions-framework-evaluate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tristan Williams, Franziska Weeber, Sebastian Padó, et al.*2026*
446. **[Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-singular-revealing-value-multiple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenbo Zhang, Hengrui Cai, Wenyu Chen*2026*
447. **[Beyond the Token: Correcting the Tokenization Bias in XAI via Morphologically-Aligned Projection](https://md.research.elamur.ai/free/en/papers/yagiz-2026-beyond-token-correcting-tokenization-bias/) [Workshop Natural Language Processing for Turkic Languages](https://md.research.elamur.ai/free/en/venues/sigturk/)**Muhammet Anil Yagiz, Fahrettin Horasan*2026*
448. **[Bridging Linguistic Structure and Mechanistic Interpretability for Conceptual Interpretation in Language Models](https://md.research.elamur.ai/free/en/papers/aljaafari-2026-bridging-linguistic-structure-mechanistic-interpretability/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Nura Aljaafari, Danilo Carvalho, Andre Freitas*2026*
449. [**CEI: A Benchmark for Evaluating Pragmatic Reasoning in Language Models arXiv:2603.09993**Jon Chun, Hannah Sussman, Adrian Mangine, et al.*2026*](https://md.research.elamur.ai/free/en/papers/chun-2026-cei-benchmark-evaluating-pragmatic-reasoning/)
450. **[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*
451. **[CIA: Inferring the Communication Topology from LLM-based Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/wu-2026-cia-inferring-communication-topology-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongxuan Wu, Xixun Lin, He Zhang, et al.*2026*
452. **[Compositional Meaning Representations in LLMs: a Critical Review of Probing Studies](https://md.research.elamur.ai/free/en/papers/marro-2026-compositional-meaning-representations-llms-critical/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Rémy Marro*2026*
453. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
454. **[Do Transformers Grok Succinct Algorithms? Mechanistic Evidence for Counting Circuits](https://md.research.elamur.ai/free/en/papers/zhao-2026-do-transformers-grok-succinct-algorithms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizheng Zhao*2026*
455. **[Evaluating Language Model Pluralism through In-the-wild Crowd Discussions](https://md.research.elamur.ai/free/en/papers/mundada-2026-evaluating-language-model-pluralism-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gagan Mundada, Rohan Surana, Nandhini Swaminathan, et al.*2026*
456. **[Evaluating LLM Style Transfer Through Readability-Based Age Assessments](https://md.research.elamur.ai/free/en/papers/maro-2026-evaluating-llm-style-transfer-through/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Maria Di Maro, Antonio Origlia, Leonilda Bilo, et al.*2026*
457. **[FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation](https://md.research.elamur.ai/free/en/papers/siddika-2026-fedreft-federated-representation-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fatema Siddika, Md Anwar Hossen, Juan Pablo Munoz, et al.*2026*
458. **[Fiction Flows: A Replication and Reinterpretation of Narrative Sequentiality](https://md.research.elamur.ai/free/en/papers/piper-2026-fiction-flows-replication-reinterpretation-narrative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Andrew Piper, Sil Hamilton, Haiqi Zhou, et al.*2026*
459. **[FINEST: Improving LLM Responses to Sensitive Topics Through Fine-Grained Evaluation](https://md.research.elamur.ai/free/en/papers/oh-2026-finest-improving-llm-responses-sensitive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Juhyun Oh, Nayeon Lee, Chani Jung, et al.*2026*
460. [**From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector arXiv:2608.17827**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-global-benchmarks-local-evaluations-benchmarking/)
461. **[From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-insight-action-novel-framework-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ling Shi, Xinwei Wu, Xiaohu Zhao, et al.*2026*
462. **[From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?](https://md.research.elamur.ai/free/en/papers/mueller-2026-isolation-entanglement-when-do-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aaron Mueller, Andrew Lee, Shruti Joshi, et al.*2026*
463. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
464. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
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 Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.*2026*
467. **[I Don't Need Solution. I Need Emotional Support : Empathetic LLMs based on Emotional Validation](https://md.research.elamur.ai/free/en/papers/son-2026-i-don-t-need-solution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Suhyune Son, Jungwoo Lim, Myunghoon Kang, et al.*2026*
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470. **[Large Language Models Are Bad Dice Players: LLMs Struggle to Generate Random Numbers from Statistical Distributions](https://md.research.elamur.ai/free/en/papers/zhao-2026-large-language-models-are-bad/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minda Zhao, Yilun Du, Mengyu Wang*2026*
471. **[Lexical Popularity: Quantifying the Impact of Pre-training for LLM Performance](https://md.research.elamur.ai/free/en/papers/ruzzetti-2026-lexical-popularity-quantifying-impact-pre/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Elena Sofia Ruzzetti, Fabio Massimo Zanzotto, Tommaso Caselli*2026*
472. **[LIBERTy: A Causal Framework for Benchmarking Concept-Based Explanations of LLMs with Structural Counterfactuals](https://md.research.elamur.ai/free/en/papers/toker-2026-liberty-causal-framework-benchmarking-concept/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gilat Toker, Nitay Calderon, Ohad Amosy, et al.*2026*
473. **[Linguistic symptoms: retrieval-augmented generation and reasoning in LLMs under Portuguese–English variation in medical contexts (Sintomas Linguísticos: Geração Aumentada por Recuperação e Raciocínio em LLMs sob a Variação Português-Inglês em Contextos Médicos)](https://md.research.elamur.ai/free/en/papers/moura-2026-sintomas-linguisticos-geracao-aumentada-por/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Guilherme Vianna de Moura, Gabriel Assis, Aline Paes*2026*
474. **[Markovian Linguistic-Temporal Bridge: Unlocking the Potential of LLMs for Time Series Forecasting](https://md.research.elamur.ai/free/en/papers/sun-2026-markovian-linguistic-temporal-bridge-unlocking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Sun, Kai Zhang, Xuejun Jiang, et al.*2026*
475. **[Mechanistic Interpretability Meets Cognitive Linguistics: Modelling Locative Image Schemas in the Circuit Framework](https://md.research.elamur.ai/free/en/papers/proietti-2026-mechanistic-interpretability-meets-cognitive-linguistics/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mattia Proietti, Afra Alishahi, Grzegorz Chrupała, et al.*2026*
476. **[On the Cultural Anachronism and Temporal Reasoning in Vision Language Models](https://md.research.elamur.ai/free/en/papers/ranjan-2026-cultural-anachronism-temporal-reasoning-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mukul Ranjan, Prince Jha, Khushboo Kumari, et al.*2026*
477. **[Persona-Aware Evaluation of Cognitive Bias in LLMs: From Benchmark to Applied Decision-Making](https://md.research.elamur.ai/free/en/papers/yoshikawa-2026-persona-aware-evaluation-cognitive-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Katsumasa Yoshikawa, Junya Takayama, Takato Yamazaki*2026*
478. **[Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/asgari-2026-quantifying-metric-model-agreement-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arash Asgari, Huan Wu, Amirreza Naziri, et al.*2026*
479. **[Reference Attack: A New Cross-Modal Jailbreaking Attack against Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-reference-attack-new-cross-modal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Yifei Fu, Jiayi Gao*2026*
480. **[Revisiting German Complex Word Identification: Contextualized LLMs and Feature Injection](https://md.research.elamur.ai/free/en/papers/schomacker-2026-revisiting-german-complex-word-identification/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Thorben Schomacker, Seid Muhie Yimam, Chris Biemann, et al.*2026*
481. [**Sentiment Classification of Gaza War Headlines: A Comparative Analysis of Large Language Models and Arabic Fine-Tuned BERT Models arXiv:2604.08566 · SSRN (2026)**Amr Eleraqi; Hager H. Mustafa;, Abdul Hadi N. Ahmed*2026*](https://md.research.elamur.ai/free/en/papers/eleraqi-2026-sentiment-classification-gaza-war-headlines/)
482. **[Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning](https://md.research.elamur.ai/free/en/papers/wan-2026-test-time-scaling-multimodal-foundation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cong Wan, Ying He, Zhongzhan Huang, et al.*2026*
483. [**The Validity of Coreference-based Evaluations of Natural Language Understanding arXiv:2602.16200**Ian Porada*2026*](https://md.research.elamur.ai/free/en/papers/porada-2026-validity-coreference-based-evaluations-natural/)
484. **[Toward Cognitive Alignment in Large Language Models: Integrating Linguistic Theory and Human Data](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-cognitive-alignment-large-language-models/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Wajdi Zaghouani*2026*
485. **[Toward Dialect-Aware Safety Evaluation for Arabic Large Language Models](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-dialect-aware-safety-evaluation-arabic/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Wajdi Zaghouani*2026*
486. **[Toward Responsible and Epistemically Grounded Multilingual LLMs for Computational Social Science and Humanities](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-responsible-epistemically-grounded-multilingual-llms/) [Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LREC](https://md.research.elamur.ai/free/en/venues/llms4ssh/)**Wajdi Zaghouani*2026*
487. **[Towards IP Intelligence: Benchmarking Large Language Models on Intellectual Property Knowledge and Practice](https://md.research.elamur.ai/free/en/papers/wang-2026-ip-intelligence-benchmarking-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyao Wang, Guhong Chen, Hongbo Wang, et al.*2026*
488. **[Vinclat: Evaluating Reasoning, Cognition and Culture in One Game](https://md.research.elamur.ai/free/en/papers/pamies-2026-vinclat-evaluating-reasoning-cognition-culture/) [Workshop on Multilingual Multicultural Evaluation](https://md.research.elamur.ai/free/en/venues/mme/)**Marc Pàmies, Javier Aula-Blasco, Aitor Gonzalez-Agirre, et al.*2026*
489. **[When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question Answering](https://md.research.elamur.ai/free/en/papers/wong-2026-when-models-decide-when-they/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hugh Mee Wong, Rick Nouwen, Albert Gatt*2026*
490. [**Embodied Intelligence Systems Based on Large Models: A Survey (基于大模型的具身智能系统综述) Acta Automatica Sinica (自动化学报)**Wensheng Wang (王文晟), Ning Tan (谭宁), Kai Huang (黄凯), et al.*2025*](https://md.research.elamur.ai/free/en/papers/wang-2025-embodied-intelligence-systems/)
491. **[From Measurement to Mitigation: Exploring the Transferability of Debiasing Approaches to Gender Bias in Maltese Language Models](https://md.research.elamur.ai/free/en/papers/galea-2025-measurement-mitigation-exploring-transferability-debiasing/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Melanie Galea, Claudia Borg*2025*
492. **[The Need for Robust and Inclusive Benchmarks in Evaluating LLMs on Arabic Text](https://md.research.elamur.ai/free/en/papers/rayes-2025-need-robust-inclusive-benchmarks-evaluating/) [International Conference on Natural Language and Speech Processing](https://md.research.elamur.ai/free/en/venues/icnlsp/)**Lubana Al Rayes, Ashraf Elnagar*2025*
493. **[Survey on Hallucinations in Large Language Models (大语言模型的幻觉问题研究综述)](https://md.research.elamur.ai/free/en/papers/liu-2024-hallucinations-large-language/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zeyuan Liu (刘泽垣), Pengjiang Wang (王鹏江), Xiaobin Song (宋晓斌), et al.*2024*
494. [**Questions After ChatGPT: Opportunities and Challenges of Very Large Pre-trained Models (问答ChatGPT之后: 超大预训练模型的机遇和挑战) Acta Automatica Sinica (自动化学报)**Jingwei Lu (卢经纬), Chao Guo (郭超), Xingyuan Dai (戴星原), et al.*2023*](https://md.research.elamur.ai/free/en/papers/lu-2023-questions-after-chatgpt/)

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