---
title: "Who cites Nelson Elhage — page 8 — 3,081 papers of our library"
description: "3,081 papers of the Elamur Research library cite the works of Nelson Elhage, found in their bibliographies · page 8 of 9 · 701–800; the most…"
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---
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# Who cites Nelson Elhage

3,930 citations of their works from 3,081 papers of our library (of the 149,439 whose bibliographies we read) · 868 with a page here, the most cited first · page 8 of 9 · 701–800 · [← Nelson Elhage](https://md.research.elamur.ai/free/en/authors/nelson-elhage/)

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701. **[SafeSearch: Do Not Trade Safety for Utility in LLM Search Agents](https://md.research.elamur.ai/free/en/papers/zhan-2026-safesearch-do-not-trade-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiusi Zhan, Angeline Budiman-Chan, Abdelrahman Zayed, et al.*2026 · 1 citation*
702. **[Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation Task](https://md.research.elamur.ai/free/en/papers/petersen-2026-sense-sensitivity-reasoning-models-are/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Dawson Petersen, Abhishek Purushothama, Nathan Schneider*2026 · 1 citation*
703. **[Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier](https://md.research.elamur.ai/free/en/papers/zhong-2026-solve-detect-verify-inference-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianyuan Zhong, Zeju Li, Zhijian Xu, et al.*2026 · 1 citation*
704. **[Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs](https://md.research.elamur.ai/free/en/papers/maraia-2026-sounding-vs-being-expert-disentangling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gabriele Maraia, Fabio Massimo Zanzotto, Leonardo Ranaldi*2026 · 1 citation*
705. **[SSA: Improving Performance With a Better Scoring Function](https://md.research.elamur.ai/free/en/papers/naim-2026-ssa-improving-performance-better-scoring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Omar Naim, Swarnadeep Bhar, Jerome Bolte, et al.*2026 · 1 citation*
706. **[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*
707. **[SycoBench-600: Measuring Sycophancy and Correction Selectivity in LLM Assistants](https://md.research.elamur.ai/free/en/papers/sinha-2026-sycobench-600-measuring-sycophancy-correction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debu Sinha*2026 · 1 citation*
708. **[Test of Time: Rethinking Temporal Signal of Benchmark Contamination](https://md.research.elamur.ai/free/en/papers/zhang-2026-test-time-rethinking-temporal-signal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Terry Jingchen Zhang, Gopal Dev, Ning Wang, et al.*2026 · 1 citation*
709. **[The Pluralistic Moral Gap: Understanding Moral Judgment and Value Differences between Humans and Large Language Models](https://md.research.elamur.ai/free/en/papers/russo-2026-pluralistic-moral-gap-understanding-moral/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Giuseppe Russo, Debora Nozza, Paul Röttger, et al.*2026 · 1 citation*
710. **[Trajectory Signatures of Deception in Large Language Models](https://md.research.elamur.ai/free/en/papers/mothukuri-2026-trajectory-signatures-deception-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viraaji Mothukuri, Reza M. Parizi*2026 · 1 citation*
711. **[Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-understanding-mitigating-political-stance-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayi Zhang, Shu Yang, Junchao Wu, et al.*2026 · 1 citation*
712. **[Unleashing the Unseen: Harnessing Benign Datasets for Jailbreaking Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-unleashing-unseen-harnessing-benign-datasets/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wei Zhao, Zhe Li, Yige Li, et al.*2026 · 1 citation*
713. **[Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/luo-2026-utility-oriented-visual-evidence-selection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiqing Luo, Zongye Hu, Xiao Wang, et al.*2026 · 1 citation*
714. **[What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies](https://md.research.elamur.ai/free/en/papers/zhou-2026-what-exactly-do-children-receive/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Zhenghao Zhou, William Dai, Maya Viswanathan, et al.*2026 · 1 citation*
715. **[When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias](https://md.research.elamur.ai/free/en/papers/zou-2026-when-vision-language-models-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh, et al.*2026 · 1 citation*
716. **[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*
717. **[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*
718. [**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/)
719. [**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/)
720. **[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*
721. **[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*
722. **[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*
723. **[AI Safety Lost in Translation: Evaluating the Effectiveness of English-Italian Cross-Lingual LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/wu-2026-ai-safety-lost-translation-evaluating/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Alessio Wu, Martim Brandao*2026*
724. **[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*
725. **[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*
726. **[At Your Own PACE: A Causal Framework for Evaluating EQ in LLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-your-own-pace-causal-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Lyu, Shengling Wang, Ke Chao, et al.*2026*
727. **[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*
728. **[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*
729. **[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*
730. **[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*
731. **[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*
732. **[Bridging Cognition and Affect: Emotion-Aware Opinion Summarization using LLMs](https://md.research.elamur.ai/free/en/papers/attri-2026-bridging-cognition-affect-emotion-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arnav Attri, Anuj Attri*2026*
733. **[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*
734. **[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*
735. **[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*
736. **[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*
737. **[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*
738. **[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*
739. **[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*
740. **[Compact Example-Based Explanations for Language Models](https://md.research.elamur.ai/free/en/papers/schoenegger-2026-compact-example-based-explanations-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Loris Schoenegger, Benjamin Roth*2026*
741. [**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/)
742. **[CoopValue: Revealing LLM Value Preferences Through Multi-Agent Cooperation](https://md.research.elamur.ai/free/en/papers/tang-2026-coopvalue-revealing-llm-value-preferences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zee Hen Tang, Mi-Yen Yeh*2026*
743. **[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*
744. **[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*
745. **[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*
746. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*
747. **[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*
748. **[Data Efficient RLVR via Off-Policy Influence Guidance](https://md.research.elamur.ai/free/en/papers/zhu-2026-data-efficient-rlvr-off-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erle Zhu, Dazhi Jiang, Yuan Wang, et al.*2026*
749. **[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*
750. **[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*
751. **[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*
752. **[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*
753. **[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*
754. **[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*
755. **[DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deference](https://md.research.elamur.ai/free/en/papers/rabbani-2026-dialdefer-framework-detecting-mitigating-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parisa Rabbani, Priyam Sahoo, Ruben Mathew, et al.*2026*
756. **[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*
757. **[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*
758. **[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*
759. **[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*
760. **[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*
761. **[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*
762. **[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*
763. **[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*
764. **[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*
765. **[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*
766. **[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*
767. **[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*
768. **[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*
769. **[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*
770. **[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*
771. **[Faithfulness vs. Safety: Evaluating LLM Behavior Under Counterfactual Medical Evidence](https://md.research.elamur.ai/free/en/papers/mo-2026-faithfulness-vs-safety-evaluating-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaijie Mo, Siddhartha Venkatayogi, Chantal Shaib, et al.*2026*
772. **[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*
773. **[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*
774. **[From Explicit to Implicit: A Theoretical Framework and Transfer Method for Preference Internalization in Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-explicit-implicit-theoretical-framework-transfer/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Binrui Wang, Yongping Du, Yu Pei, et al.*2026*
775. **[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*
776. **[Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-generalizing-trust-weak-strong-trustworthiness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lillian Sun, Martin Pawelczyk, Zhenting Qi, et al.*2026*
777. **[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*
778. **[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*
779. **[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*
780. **[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*
781. **[How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities](https://md.research.elamur.ai/free/en/papers/xu-2026-how-controllable-are-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Kewei Xu, Haoming Xu, et al.*2026*
782. **[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*
783. [**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/)
784. **[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*
785. **[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*
786. **[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*
787. **[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*
788. **[Interpretable Semantic Gradients in SSD: A PCA Sweep Approach and a Case Study on AI Discourse](https://md.research.elamur.ai/free/en/papers/plisiecki-2026-interpretable-semantic-gradients-ssd-pca/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hubert Plisiecki, Maria Leniarska, Jan Piotrowski, et al.*2026*
789. **[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*
790. **[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*
791. **[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*
792. **[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*
793. **[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*
794. **[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*
795. **[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*
796. **[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*
797. **[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*
798. **[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*
799. **[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*
800. **[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*

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