---
title: "Who cites Nova DasSarma — page 9 — 3,065 citing papers"
description: "3,065 papers of the Elamur Research library cite the works of Nova DasSarma, found in their bibliographies · page 9 of 9 · 801–857; the most…"
canonical: "https://research.elamur.ai/free/en/authors/nova-dassarma/cited-by/page/9/"
---
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# Who cites Nova DasSarma

3,936 citations of their works from 3,065 papers of our library (of the 149,439 whose bibliographies we read) · 857 with a page here, the most cited first · page 9 of 9 · 801–857 · [← Nova DasSarma](https://md.research.elamur.ai/free/en/authors/nova-dassarma/)

[← prev](https://md.research.elamur.ai/free/en/authors/nova-dassarma/cited-by/page/8/) [1](https://md.research.elamur.ai/free/en/authors/nova-dassarma/cited-by/) … [8](https://md.research.elamur.ai/free/en/authors/nova-dassarma/cited-by/page/8/) **9**

801. **[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*
802. **[Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not Stable](https://md.research.elamur.ai/free/en/papers/tang-2026-probing-plasticity-correlation-llm-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenheng Tang, Qihua Pan, Jingya Shen, et al.*2026*
803. **[Quantifying and Mitigating Socially Desirable Responding in LLMs: A Desirability-Matched Graded Forced-Choice Psychometric Study](https://md.research.elamur.ai/free/en/papers/okada-2026-quantifying-mitigating-socially-desirable-responding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kensuke Okada, Yui Furukawa, Kyosuke Bunji*2026*
804. **[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*
805. **[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*
806. **[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*
807. **[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*
808. **[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*
809. **[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*
810. **[Rendering Data Unlearnable by Exploiting LLM Alignment Mechanisms](https://md.research.elamur.ai/free/en/papers/zhang-2026-rendering-data-unlearnable-exploiting-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruihan Zhang, Jun Sun*2026*
811. **[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*
812. **[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*
813. **[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*
814. **[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*
815. **[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*
816. **[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*
817. **[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*
818. **[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*
819. [**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/)
820. **[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*
821. **[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*
822. **[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*
823. **[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*
824. **[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*
825. **[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*
826. **[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*
827. **[Tandem Training for Language Models](https://md.research.elamur.ai/free/en/papers/west-2026-tandem-training-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Robert West, Ashton Anderson, Ece Kamar, et al.*2026*
828. **[Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward Modeling](https://md.research.elamur.ai/free/en/papers/pathmanathan-2026-teach-reward-model-correct-itself/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pankayaraj Pathmanathan, Furong Huang*2026*
829. **[Teaching Values to Machines: Simulating Human-Like Behavior in LLMs](https://md.research.elamur.ai/free/en/papers/yehudai-2026-teaching-values-machines-simulating-human/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Asaf Yehudai, Naama Rozen, Ariel Gera*2026*
830. **[The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-art-mis-alignment-how-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Zhang, Hongwei Li, Yun Shen, et al.*2026*
831. **[The Impact of Off-Policy Training Data on Probe Generalisation](https://md.research.elamur.ai/free/en/papers/skapars-2026-impact-off-policy-training-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrians Skapars, Nathalie Maria Kirch, Samuel Dower, et al.*2026*
832. **[The Imperfective Paradox in Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-imperfective-paradox-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bolei Ma, Yusuke Miyao*2026*
833. **[The Inner Monologue of Language Models: When Reasoning Traces Reveal More Than They Hide](https://md.research.elamur.ai/free/en/papers/singla-2026-inner-monologue-language-models-when/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pratham Singla, Shivank Garg, Ayush Singh, et al.*2026*
834. **[ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning](https://md.research.elamur.ai/free/en/papers/smirnov-2026-thinkbooster-unified-framework-seamless-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.*2026*
835. **[Thinking Twice Makes Large Language Models Safer and More Helpful](https://md.research.elamur.ai/free/en/papers/mou-2026-thinking-twice-makes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.*2026*
836. **[Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models](https://md.research.elamur.ai/free/en/papers/shah-2026-too-nice-tell-truth-quantifying/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arya Shah, Deepali Mishra, Chaklam Silpasuwanchai*2026*
837. **[Topology-Enhanced Alignment for Large Language Models: Trajectory Topology Loss and Topological Preference Optimization](https://md.research.elamur.ai/free/en/papers/pan-2026-topology-enhanced-alignment-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yurui Pan, Ke Xu, Bo Peng*2026*
838. **[Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement](https://md.research.elamur.ai/free/en/papers/zhong-2026-consistent-world-models-multi-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qimin Zhong, Hao Liao, Haiming Qin, et al.*2026*
839. **[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*
840. **[Toxic Subword Pruning for Dialogue Response Generation on Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2026-toxic-subword-pruning-dialogue-response/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Hongyuan Adam Lu, Wai Lam*2026*
841. **[TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG](https://md.research.elamur.ai/free/en/papers/lu-2026-tpa-next-token-probability-attribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengqian Lu, Jie Lu, Anjin Liu, et al.*2026*
842. **[TrajGuard: Streaming Hidden-state Trajectory Detection for Decoding-time Jailbreak Defense](https://md.research.elamur.ai/free/en/papers/liu-2026-trajguard-streaming-hidden-state-trajectory/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Liu, Xiaolei Liu, Xingyu Li, et al.*2026*
843. **[Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/luo-2026-two-pathways-truthfulness-intrinsic-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Luo, Guangyue Peng, Wei Li, et al.*2026*
844. **[Understanding Emergent Misalignment via Feature Superposition Geometry](https://md.research.elamur.ai/free/en/papers/minegishi-2026-understanding-emergent-misalignment-feature-superposition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gouki Minegishi, Hiroki Furuta, Takeshi Kojima, et al.*2026*
845. **[Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures](https://md.research.elamur.ai/free/en/papers/wang-2026-understanding-context-learning-beyond-transformers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shenran Wang, Timothy Tin-Long Tse, Jian Zhu*2026*
846. **[User-Assistant Bias in LLMs](https://md.research.elamur.ai/free/en/papers/pan-2026-user-assistant-bias-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Pan, Jingxuan Fan, Zidi Xiong, et al.*2026*
847. **[VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation](https://md.research.elamur.ai/free/en/papers/park-2026-vauq-vision-aware-uncertainty-quantification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.*2026*
848. **[Vertical Routing: A Cost-Efficient Collaboration Routing Framework](https://md.research.elamur.ai/free/en/papers/shen-2026-vertical-routing-cost-efficient-collaboration/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Si Shen, Peijun Shen, Danhao Zhu*2026*
849. **[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*
850. **[VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning](https://md.research.elamur.ai/free/en/papers/xiao-2026-vl-calibration-decoupled-confidence-calibration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenyi Xiao, Xinchi XU, Leilei Gan*2026*
851. **[We Are What We Repeatedly Do: Improving Long Context Instruction Following](https://md.research.elamur.ai/free/en/papers/robinette-2026-we-are-what-we-repeatedly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Preston K Robinette, Andrew Hard, Swaroop Ramaswamy, et al.*2026*
852. **[When Safety Alignment Fails to Generalize: Probing with Language Game Jailbreaks](https://md.research.elamur.ai/free/en/papers/long-2026-when-safety-alignment-fails-generalize/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zewen Long, Yu Peng, Fangming Dong, et al.*2026*
853. **[Where CoT Reasoning Commits: Entropy Traces Identify Interpretable Attention Heads](https://md.research.elamur.ai/free/en/papers/zhang-2026-where-cot-reasoning-commits-entropy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianhe Zhang, Yonghong Deng, Ping Jian, et al.*2026*
854. **[Who Plays Which Role? Protagonist Detection and Classification in Moral Discourse](https://md.research.elamur.ai/free/en/papers/sommer-2026-who-plays-which-role-protagonist/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mirko Sommer, Maria Becker*2026*
855. **[XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake Detection](https://md.research.elamur.ai/free/en/papers/ng-2026-xlsr-mambo-scaling-hybrid-mamba/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kwok-Ho Ng, Tingting Song, Yongdong WU, et al.*2026*
856. **[You Only Need One Single Token to Refine Safety Alignment](https://md.research.elamur.ai/free/en/papers/yu-2026-you-only-need-one-single/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenqian Yu, Shuo Chen, Zhijiang Li, et al.*2026*
857. [**360Zhinao Technical Report arXiv:2405.13386***2024*](https://md.research.elamur.ai/free/en/papers/360zhinao-team-2024-360zhinao-technical-report/)

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