---
title: "Who cites Tom Conerly — page 8 — 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 8 of 8 · 701–729; 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 8 of 8 · 701–729 · [← Tom Conerly](https://md.research.elamur.ai/free/en/authors/tom-conerly/)

[← prev](https://md.research.elamur.ai/free/en/authors/tom-conerly/cited-by/page/7/) [1](https://md.research.elamur.ai/free/en/authors/tom-conerly/cited-by/) … [7](https://md.research.elamur.ai/free/en/authors/tom-conerly/cited-by/page/7/) **8**

701. **[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*
702. **[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*
703. **[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*
704. **[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*
705. **[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*
706. **[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*
707. **[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*
708. **[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*
709. **[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*
710. **[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*
711. **[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*
712. **[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*
713. **[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*
714. **[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*
715. **[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*
716. **[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*
717. **[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*
718. **[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*
719. **[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*
720. **[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*
721. **[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*
722. **[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*
723. **[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*
724. **[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*
725. **[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*
726. **[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*
727. **[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*
728. **[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*
729. [**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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