---
title: "Who cites Tom Conerly — page 7 — 2,604 papers of our library"
description: "2,604 papers of the Elamur Research library cite the works of Tom Conerly, found in their bibliographies · page 7 of 8 · 601–700; the most cited first."
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---
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# Who cites Tom Conerly

2,945 citations of their works from 2,604 papers of our library (of the 149,439 whose bibliographies we read) · 729 with a page here, the most cited first · page 7 of 8 · 601–700 · [← Tom Conerly](https://md.research.elamur.ai/free/en/authors/tom-conerly/)

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601. **[Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/proebsting-2025-biases-large-language-model-elicited/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Grace Proebsting, Adam Poliak*2025 · 1 citation*
602. **[Construction Grammar Evidence for How LLMs Use Context-Directed Extrapolation to Solve Tasks](https://md.research.elamur.ai/free/en/papers/madabushi-2025-construction-grammar-evidence-how-llms/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Harish Tayyar Madabushi, Claire Bonial*2025 · 1 citation*
603. [**HAMSA: Hijacking Aligned Compact Models via Stealthy Automation arXiv:2508.16484**Alexey Krylov, Iskander Vagizov, Dmitrii Korzh, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/krylov-2025-hamsa-hijacking-aligned-compact-models/)
604. [**Safe at the Margins: A General Approach to Safety Alignment in Low-Resource English Languages — A Singlish Case Study arXiv:2502.12485**Isaac Lim, Shaun Khoo, Roy Ka-Wei Lee, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lim-2025-safe-margins-general-approach-safety/)
605. **[A Dual-Phase Self-Evolution Framework for Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-dual-phase-self-evolution-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Sun, Zekun Zhang, Shaoning Zeng*2026*
606. **[Adaptive Instruction Composition for Automated LLM Red-Teaming](https://md.research.elamur.ai/free/en/papers/zymet-2026-adaptive-instruction-composition-automated-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jesse Zymet, Andy Luo, Swapnil Shinde, et al.*2026*
607. **[AnswerCarefully: Creating a Dataset for LLM Safety in Japanese](https://md.research.elamur.ai/free/en/papers/suzuki-2026-answercarefully-creating-dataset-llm-safety/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hisami Suzuki, Satoru Katsumata, Takashi Kodama, et al.*2026*
608. **[ARF-RLHF: Adaptive Reward-Following for RLHF through Emotion-Driven Self-Supervision and Trace-Biased Dynamic Optimization](https://md.research.elamur.ai/free/en/papers/zhang-2026-arf-rlhf-adaptive-reward-following/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Zhang*2026*
609. **[Attn-GS: Attention-Guided Context Compression for Efficient Personalized LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2026-attn-gs-attention-guided-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shenglai Zeng, Tianqi Zheng, Chuan Tian, et al.*2026*
610. **[Attribute-Controlled Translation with Preference Optimization](https://md.research.elamur.ai/free/en/papers/unanue-2026-attribute-controlled-translation-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Inigo Jauregi Unanue, Najmeh Sadoughi, Vimal Bhat, et al.*2026*
611. **[Balancing Classification and Calibration Performance in Decision-Making LLMs via Calibration Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yaldiz-2026-balancing-classification-calibration-performance-decision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duygu Nur Yaldiz, Evangelia Spiliopoulou, Zheng Qi, et al.*2026*
612. **[Boosting Self-Consistency with Ranking](https://md.research.elamur.ai/free/en/papers/marina-2026-boosting-self-consistency-ranking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maria Marina, Daniil Moskovskiy, Sergey Pletenev, et al.*2026*
613. **[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*
614. **[BrowseConf: Confidence-Guided Test-Time Scaling for Web Agents](https://md.research.elamur.ai/free/en/papers/ou-2026-browseconf-confidence-guided-test-time/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Litu Ou, Kuan Li, Huifeng Yin, et al.*2026*
615. **[Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation](https://md.research.elamur.ai/free/en/papers/radharapu-2026-calibrating-llm-judges-linear-probes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.*2026*
616. **[Calibration-Aware Policy Optimization for Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-calibration-aware-policy-optimization-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqi Wang, Xingzhou Lou, Meiqi Wu, et al.*2026*
617. **[CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification](https://md.research.elamur.ai/free/en/papers/wang-2026-causaldetox-causal-head-selection-intervention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yian Wang, Yuen Chen, Agam Goyal, et al.*2026*
618. **[Cognitive Analysis Graph-Guided Multi-Turn Safety Enhancement for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-cognitive-analysis-graph-guided-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lanxue Zhang, Yuqiang Xie, Fang Fang, et al.*2026*
619. **[COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values](https://md.research.elamur.ai/free/en/papers/wu-2026-coig-p-high-quality-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Siwei Wu, JinCheng Ren, Xeron Du, et al.*2026*
620. **[Credal Concept Bottleneck Models for Epistemic–Aleatoric Uncertainty Decomposition](https://md.research.elamur.ai/free/en/papers/mukherjee-2026-credal-concept-bottleneck-models-epistemic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tanmoy Mukherjee, Thomas Bailleux, Pierre Marquis, et al.*2026*
621. **[Cross-Lingual Bias in Large Language Models: A Comparative Analysis of English and Swahili](https://md.research.elamur.ai/free/en/papers/zhang-2026-cross-lingual-bias-large-language/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Ruolei Zhang, Teddy Njuguna, Yue Feng*2026*
622. **[CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks](https://md.research.elamur.ai/free/en/papers/zhang-2026-crossguard-safeguarding-mllms-against-joint/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xu Zhang, Hao Li, Zhichao Lu*2026*
623. **[DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training](https://md.research.elamur.ai/free/en/papers/pan-2026-dart-mitigating-harm-drift-difference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwen Pan, Zihan Liang, Jad Kabbara, et al.*2026*
624. **[Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment](https://md.research.elamur.ai/free/en/papers/xue-2026-deactivating-refusal-triggers-understanding-mitigating/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Zhiyu Xue, Zimo Qi, Guangliang Liu, et al.*2026*
625. **[Debiasing Reward Models via Causally Motivated Inference-Time Intervention](https://md.research.elamur.ai/free/en/papers/shinoda-2026-debiasing-reward-models-causally-motivated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida*2026*
626. **[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*
627. **[Deliberative Searcher: Improving LLM Reliability via Reinforcement Learning with Constraints](https://md.research.elamur.ai/free/en/papers/yin-2026-deliberative-searcher-improving-llm-reliability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenyun Yin, Shujie Wang, Xuhong Wang, et al.*2026*
628. **[Detection of Adversarial Prompts with Model Predictive Entropy](https://md.research.elamur.ai/free/en/papers/rubenbauer-2026-detection-adversarial-prompts-model-predictive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Franziska Rubenbauer, Sebastian Steindl, Patrick Levi, et al.*2026*
629. **[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*
630. **[DiPS: Dialogue Policy Selection for High-Stakes Persuasion Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-dips-dialogue-policy-selection-high/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Tianyi Zhang, Mousumi Das, Abrar Anwar, et al.*2026*
631. **[DisCal: Distribution-Aware Calibration for Mathematical Reasoning Under Character-Level Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-discal-distribution-aware-calibration-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Zhang, Jiawei Zhang, Cong Gao, et al.*2026*
632. **[Disentangling Linguistic Relatedness from Task Alignment in Cross-Lingual Transfer](https://md.research.elamur.ai/free/en/papers/ahmed-2026-disentangling-linguistic-relatedness-task-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ahmed Haj Ahmed, Ruochen Zhang, Alvin C Grissom II*2026*
633. **[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*
634. **[DyBBT: Dynamic Balance via Bandit-inspired Targeting for Dialog Policy with Cognitive Dual Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-dybbt-dynamic-balance-bandit-inspired/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuyu Zhang, Yifan Wei, Jialuo Yuan, et al.*2026*
635. **[Dynamic Graph Navigation via Triplet Chains for Structure-Aware Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhao-2026-dynamic-graph-navigation-triplet-chains/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Feng Zhao, Yufei Wu, Xianggan Liu, et al.*2026*
636. **[D²-RAG: Dual-Decision Retrieval-Augmented Generation via Multi-Dimensional Uncertainty and Utility-Aware Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-d-2-rag-dual-decision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinshuo Zhang, Xiaoding Zhou, Weiyu Zhang, et al.*2026*
637. **[ECHA: Jailbreaking LVLMs via the Mismatch between Implicit Semantic Reconstruction and Explicit Safety Alignment](https://md.research.elamur.ai/free/en/papers/xu-2026-echa-jailbreaking-lvlms-mismatch-between/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenxing Xu, Junyong Jiang, Zehu Zhang, et al.*2026*
638. **[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*
639. **[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*
640. **[Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for Classification](https://md.research.elamur.ai/free/en/papers/merdjanovska-2026-evaluation-pitfalls-sparsity-limitations-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elena Merdjanovska, Omar Zaidan, Andreas Rücklé*2026*
641. **[Evolutionary Search for Automated Design of Uncertainty Quantification Methods](https://md.research.elamur.ai/free/en/papers/seleznyov-2026-evolutionary-search-automated-design-uncertainty/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.*2026*
642. **[FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs](https://md.research.elamur.ai/free/en/papers/sawczyn-2026-factselfcheck-fact-level-black-box/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Albert Sawczyn, Jakub Binkowski, Denis Janiak, et al.*2026*
643. **[Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck](https://md.research.elamur.ai/free/en/papers/zhang-2026-failure-modes-multi-hop-qa/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meiru Zhang, Zaiqiao Meng, Nigel Collier*2026*
644. **[Feeling Right vs. Being Right: How AI Sycophancy Affects Value-Laden Deliberation](https://md.research.elamur.ai/free/en/papers/ryu-2026-feeling-right-vs-being-right/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeongwoo Ryu, Soomin Kim, Jinsu Eun, et al.*2026*
645. **[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*
646. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
647. **[Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mei-2026-good-reasoning-makes-good-demonstrations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tiehua Mei, Minxuan Lv, Leiyu Pan, et al.*2026*
648. **[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*
649. **[Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization](https://md.research.elamur.ai/free/en/papers/zhao-2026-hallucinations-as-orthogonal-noise-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mingkuan Zhao, Wentao Hu, Tianchen Huang, et al.*2026*
650. **[HalluZig: Hallucination Detection using Zigzag Persistence](https://md.research.elamur.ai/free/en/papers/samaga-2026-halluzig-hallucination-detection-zigzag-persistence/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shreyas N. Samaga, Gilberto Gonzalez Arroyo, Tamal K. Dey*2026*
651. **[How Do LLMs Generate Contrastive Sentiments? A Mechanistic Perspective](https://md.research.elamur.ai/free/en/papers/nguyen-2026-how-do-llms-generate-contrastive/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Van Bach Nguyen, Jörg Schlötterer, Christin Seifert*2026*
652. [**How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline arXiv:2604.04204**Mir Tafseer Nayeem, Davood Rafiei*2026*](https://md.research.elamur.ai/free/en/papers/nayeem-2026-english-us-become-default-triangulating/)
653. **[Illusions of Confidence? Diagnosing LLM Truthfulness via Neighborhood Consistency](https://md.research.elamur.ai/free/en/papers/xu-2026-illusions-confidence-diagnosing-llm-truthfulness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoming Xu, Ningyuan Zhao, Yunzhi Yao, et al.*2026*
654. **[Improving LLM Domain Certification with Pretrained Guide Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-improving-llm-domain-certification-pretrained/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jiaqian Zhang, Zhaozhi Qian, Faroq AL-Tam, et al.*2026*
655. **[Inflated Excellence or True Performance? Rethinking Medical Diagnostic Benchmarks with Dynamic Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-inflated-excellence-or-true-performance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangxu Zhang, Lei Li, Yanyun Zhou, et al.*2026*
656. **[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*
657. **[Judging Instruction Responses in a Low-Resource Language: A Case Study on Basque](https://md.research.elamur.ai/free/en/papers/ponce-2026-judging-instruction-responses-low-resource/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**David Ponce, Harritxu Gete, Thierry Etchegoyhen, et al.*2026*
658. **[LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries](https://md.research.elamur.ai/free/en/papers/ren-2026-latentrefusal-latent-signal-refusal-unanswerable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuancheng Ren, Shijing Hu, Zhihui Lu, et al.*2026*
659. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026*
660. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026*
661. **[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*
662. **[LLM Beliefs Are in Their Heads](https://md.research.elamur.ai/free/en/papers/mendozza-2026-llm-beliefs-are-their-heads/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alessandro Corona Mendozza, Anders Søgaard*2026*
663. **[Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgments](https://md.research.elamur.ai/free/en/papers/mi-2026-logical-consistency-as-bridge-improving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Mi, Qiang Sheng, Shaofei Wang, et al.*2026*
664. **[LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-lovec-reinforcement-learning-better-verbalized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caiqi Zhang, Xiaochen Zhu, Chengzu Li, et al.*2026*
665. **[Mapping the Course for Prompt-based Structured Prediction](https://md.research.elamur.ai/free/en/papers/pauk-2026-mapping-course-prompt-based-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Matt Pauk, Maria Leonor Pacheco*2026*
666. **[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*
667. **[Mediocrity is the key for LLM as a Judge Anchor Selection](https://md.research.elamur.ai/free/en/papers/yehiya-2026-mediocrity-is-key-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shachar Don-Yehiya, Asaf Yehudai, Leshem Choshen, et al.*2026*
668. **[MERIT Feedback Elicits Better Bargaining in LLM Negotiators](https://md.research.elamur.ai/free/en/papers/oh-2026-merit-feedback-elicits-better-bargaining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jihwan Oh, Murad Aghazada, Yooju Shin, et al.*2026*
669. **[Multi-Source Emotion Annotation in Children's Language: When LLM Consensus Diverges from Human Judgment](https://md.research.elamur.ai/free/en/papers/said-2026-multi-source-emotion-annotation-children/) [Computational Affective Science (CAS) @ LREC](https://md.research.elamur.ai/free/en/venues/cas/)**Farida Said, Jeanne Villaneau*2026*
670. **[Multimodal Large Language Models for Multi-Subject In-Context Image Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-multimodal-large-language-models-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yucheng Zhou, Dubing Chen, Huan Zheng, et al.*2026*
671. **[Neuronal Insights into LLM Attacks: Targeted Neuron Tuning for Precise and Robust Vulnerability Patching](https://md.research.elamur.ai/free/en/papers/shi-2026-neuronal-insights-into-llm-attacks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dan Shi, Renren Jin, Zhuowen Han, et al.*2026*
672. **[NP-Hard Lower Bound Complexity for Semantic Self-Verification](https://md.research.elamur.ai/free/en/papers/young-2026-np-hard-lower-bound-complexity/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Robin Young*2026*
673. **[On the Additive Compositionality of Task Vectors in Vision–Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-additive-compositionality-task-vectors-vision/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuting Shi, Houjing Wei, Naoya Inoue*2026*
674. **[Pattern Enhanced Multi-Turn Jailbreaking: Exploiting Structural Vulnerabilities in Large Language Models](https://md.research.elamur.ai/free/en/papers/nihal-2026-pattern-enhanced-multi-turn-jailbreaking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ragib Amin Nihal, Rui Wen, Kazuhiro Nakadai, et al.*2026*
675. **[Pause or Fabricate? Training Language Models for Grounded Reasoning](https://md.research.elamur.ai/free/en/papers/qiu-2026-pause-or-fabricate-training-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiwen Qiu, Linjuan Wu, Yizhou Liu, et al.*2026*
676. **[PersonaArena: Dynamic Simulation for Evaluating and Enhancing Persona-Level Role-Playing in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-personaarena-dynamic-simulation-evaluating-enhancing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenlong Shi, Jianxun Lian, Mingqi Wu, et al.*2026*
677. **[PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning](https://md.research.elamur.ai/free/en/papers/liu-2026-pretrainrl-alleviating-factuality-hallucination-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Langming Liu, Kangtao Lv, Haibin Chen, et al.*2026*
678. **[Probing Social Identity Bias in Chinese LLMs with Gendered Pronouns and Social Groups](https://md.research.elamur.ai/free/en/papers/liu-2026-probing-social-identity-bias-chinese/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Geng Liu, Li Feng, Junjie Mu, et al.*2026*
679. **[QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/qu-2026-quantumqa-enhancing-scientific-reasoning-physics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, et al.*2026*
680. **[QueerGen: How LLMs Reflect Societal Norms on Gender and Sexuality in Sentence Completion Task](https://md.research.elamur.ai/free/en/papers/sosto-2026-queergen-how-llms-reflect-societal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mae Sosto, Delfina S. Martinez Pandiani, Laura Hollink*2026*
681. **[RAMP: Risk-Aware Multi-Turn Planning for Jailbreak Red-Teaming](https://md.research.elamur.ai/free/en/papers/liu-2026-ramp-risk-aware-multi-turn/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yize Liu, Yunyun Hou, Aina Sui*2026*
682. **[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*
683. **[Reflect, Rewrite, Repeat: How Simple Arithmetic Enables Advanced Reasoning in Small Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-reflect-rewrite-repeat-how-simple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mengdie Flora Wang, Haochen Xie, Mun Young Kim, et al.*2026*
684. **[Rejection-to-Acceptance Transition: Model Editing-Based Jailbreak Backdoor Injection Not Limited to Few Output Tokens](https://md.research.elamur.ai/free/en/papers/yang-2026-rejection-acceptance-transition-model-editing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiji Yang, Min Cai, Hao Xiong, et al.*2026*
685. **[Resonant Context Anchoring: Decoupling Attention Routing and Signal Gain at Inference Time](https://md.research.elamur.ai/free/en/papers/zhao-2026-resonant-context-anchoring-decoupling-attention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mingkuan Zhao, Yide Gao, Wentao Hu, et al.*2026*
686. **[Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty](https://md.research.elamur.ai/free/en/papers/xiao-2026-revisiting-self-play-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.*2026*
687. **[RFS-Guard: Detecting Reasoning Hallucinations via Cross-Phase Routing Focus in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-rfs-guard-detecting-reasoning-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihang Liu, Fang Zhouhua, Hui Liu, et al.*2026*
688. **[RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-routemoa-dynamic-routing-without-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jize Wang, Han Wu, Zhiyuan You, et al.*2026*
689. **[S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language Models](https://md.research.elamur.ai/free/en/papers/shukla-2026-s2h-dpo-hardness-aware-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nitish Shukla, Surgan Jandial, Arun Ross*2026*
690. **[Safe-FedLLM: Delving into the Safety of Federated Large Language Models](https://md.research.elamur.ai/free/en/papers/tao-2026-safe-fedllm-delving-into-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingxiang Tao, Yu Tian, Wenxuan Tu, et al.*2026*
691. **[Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-safeguarding-llm-fine-tuning-push/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haozhong Wang, Zhuo Li, Yibo Yang, et al.*2026*
692. **[SafeSteer: A Decoding-level Defense Mechanism for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2026-safesteer-decoding-level-defense-mechanism/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyi Zeng, Xue Yang, Jingyuan Zhang, et al.*2026*
693. [**SalamahBench: Dialect and Category Level Safety Evaluation of Arabic Language Models arXiv:2603.04410**Omar Abdelnasser, Fatemah Alharbi, Khaled Khasawneh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abdelnasser-2026-salamahbench-dialect-category-level-safety/)
694. **[SD-E2: Semantic Exploration for Reasoning Under Token Budgets](https://md.research.elamur.ai/free/en/papers/mishra-2026-sd-e2-semantic-exploration-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kshitij Mishra, Nils Lukas, Salem Lahlou*2026*
695. **[SEA-SafeguardBench: Culturally Grounded Safety Benchmark for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/tasawong-2026-sea-safeguardbench-culturally-grounded-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Panuthep Tasawong, Jian Gang Ngui, Alham Fikri Aji, et al.*2026*
696. **[See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers](https://md.research.elamur.ai/free/en/papers/xia-2026-see2refine-vision-language-feedback-improves/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ding Xia, Xinyue Gui, Mark Colley, et al.*2026*
697. **[Self-Guided Alignment: Adaptive Preference Sensing for Multi-Objective Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-self-guided-alignment-adaptive-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Wang, Zhanyang Liu, Taotao Zhou, et al.*2026*
698. **[Sem-DPO: Mitigating Semantic Inconsistency in Preference Optimization for Prompt Engineering](https://md.research.elamur.ai/free/en/papers/mohamed-2026-sem-dpo-mitigating-semantic-inconsistency/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anas Mohamed, Azal Ahmad Khan, Xinran Wang, et al.*2026*
699. **[Semantic, Syntactic, Lexical: What Makes QA Augmentation Work in Limited Quantity?](https://md.research.elamur.ai/free/en/papers/rachmat-2026-semantic-syntactic-lexical-what-makes/) [Workshop on Structured Linguistic Data and Evaluation (SLiDE)](https://md.research.elamur.ai/free/en/venues/slide/)**Benedictus Kent Rachmat, Thomas Gerald, Takuya Nakamura, et al.*2026*
700. **[Soft Head Selection for Injecting ICL-Derived Task Embeddings](https://md.research.elamur.ai/free/en/papers/park-2026-soft-head-selection-injecting-icl/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jungwon Park, Jimyeong Kim, Changin Choi, et al.*2026*

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