--- title: "Who cites Linear Representations of — 56 citing papers" description: "56 papers of the Elamur Research library cite «Linear Representations of Sentiment in Large Language Models», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Linear Representations of Sentiment in Large…](https://md.research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/) / cited by # Who cites «Linear Representations of Sentiment in Large Language Models» 56 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Linear Representations of Sentiment in Large Language Models»](https://md.research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/) 1. [**Refusal in Language Models Is Mediated by a Single Direction arXiv:2406.11717**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/) 2. [**The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets arXiv:2310.06824**Samuel Marks, Max Tegmark*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/marks-2023-geometry-truth-emergent-linear-structure/) 3. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/) 4. **[CausalGym: Benchmarking causal interpretability methods on linguistic tasks](https://md.research.elamur.ai/free/en/papers/arora-2024-causalgym-benchmarking-causal-interpretability-methods/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aryaman Arora, Dan Jurafsky, Christopher Potts*2024 · 38 citations* 5. **[Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations](https://md.research.elamur.ai/free/en/papers/ji-2025-calibrating-verbal-uncertainty-as-linear/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziwei Ji, Lei Yu, Yeskendir Koishekenov, et al.*2025 · 11 citations* 6. **[Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipeline](https://md.research.elamur.ai/free/en/papers/lu-2025-paths-not-taken-understanding-mending/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Meng Lu, Ruochen Zhang, Carsten Eickhoff, et al.*2025 · 9 citations* 7. **[The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation Analysis](https://md.research.elamur.ai/free/en/papers/mueller-2026-quest-right-mediator-surveying-mechanistic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aaron Mueller, Jannik Brinkmann, Millicent Li, et al.*2026 · 7 citations* 8. **[Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics](https://md.research.elamur.ai/free/en/papers/xu-2026-why-steering-works-unified-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Chenyan WU, Hengyu Sun, et al.*2026 · 1 citation* 9. **[AdaptiveK: Complexity-Driven Sparse Autoencoders for Interpretable Language Model Representations](https://md.research.elamur.ai/free/en/papers/yao-2026-adaptivek-complexity-driven-sparse-autoencoders/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifei Yao, Hanrong Zhang, Mengnan Du*2026* 10. **[Graph-Based Alternatives to LLMs for Human Simulation](https://md.research.elamur.ai/free/en/papers/suh-2026-graph-based-alternatives-llms-human/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Suhong Moon, Serina Chang*2026* 11. **[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* 45 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/) — Linear Representations of Sentiment in Large Language Models