---
title: "Who cites Daniel Paleka — 302 papers of our library"
description: "302 papers of the Elamur Research library cite the works of Daniel Paleka, found in their bibliographies; the most cited first."
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---
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# Who cites Daniel Paleka

309 citations of their works from 302 papers of our library (of the 149,439 whose bibliographies we read) · 95 with a page here, the most cited first · [← Daniel Paleka](https://md.research.elamur.ai/free/en/authors/daniel-paleka/)

1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
3. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 280 citations*
4. [**LawBench: Benchmarking Legal Knowledge of Large Language Models arXiv:2309.16289**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 188 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
5. **[WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 165 citations*
6. [**Detecting Language Model Attacks with Perplexity arXiv:2308.14132**Gabriel Alon, Michael Kamfonas*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/alon-2023-detecting-language-model-attacks-perplexity/)
7. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/)
8. [**Platypus: Quick, Cheap, and Powerful Refinement of LLMs arXiv:2308.07317**Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz*2023 · 117 citations*](https://md.research.elamur.ai/free/en/papers/lee-2023-platypus-quick-cheap-powerful-refinement/)
9. **[GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 108 citations*
10. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/)
11. [**Can LLM-Generated Misinformation Be Detected? arXiv:2309.13788**Canyu Chen, Kai Shu*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-llm-generated-misinformation-detected/)
12. [**Nemotron-4 340B Technical Report arXiv:2406.11704**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
13. [**FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI arXiv:2411.04872**Elliot Glazer, Ege Erdil, Tamay Besiroglu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/glazer-2024-frontiermath-benchmark-evaluating-advanced-mathematical/)
14. **[WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-wildteaming-scale-wild-jailbreaks-adversarially/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Liwei Jiang, Kavel Rao, Seungju Han, et al.*2024 · 92 citations*
15. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
16. [**PaperBench: Evaluating AI's Ability to Replicate AI Research arXiv:2504.01848**Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.*2025 · 86 citations*](https://md.research.elamur.ai/free/en/papers/starace-2025-paperbench-evaluating-ai-s/)
17. **[Evaluating Mathematical Reasoning Beyond Accuracy](https://md.research.elamur.ai/free/en/papers/xia-2024-evaluating-mathematical-reasoning-accuracy/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Shijie Xia, Xuefeng Li, Yixin Liu, et al.*2024 · 85 citations*
18. [**HelpSteer2: Open-source dataset for training top-performing reward models arXiv:2406.08673**Zhilin Wang, Yi Dong, Olivier Delalleau, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-helpsteer2-open-source-dataset-training/)
19. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 76 citations*
20. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
21. [**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/)
22. **[Aligner: Efficient Alignment by Learning to Correct](https://md.research.elamur.ai/free/en/papers/ji-2024-aligner-efficient-alignment-learning-correct/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Boyuan Chen, Hantao Lou, et al.*2024 · 69 citations*
23. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
24. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
25. [**CMB: A Comprehensive Medical Benchmark in Chinese arXiv:2308.08833**Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-cmb-comprehensive-medical-benchmark/)
26. [**GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements arXiv:2402.10963**Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-glore-where-improve-llm-reasoning/)
27. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
28. **[Benchmarking Distributional Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/meister-2025-benchmarking-distributional-alignment-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto*2025 · 35 citations*
29. **[The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It](https://md.research.elamur.ai/free/en/papers/yong-2025-state-multilingual-llm-safety-research/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.*2025 · 25 citations*
30. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
31. [**GameBench: Evaluating Strategic Reasoning Abilities of LLM Agents arXiv:2406.06613**Anthony Costarelli, Mat Allen, Roman Hauksson, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/costarelli-2024-gamebench-evaluating-strategic-reasoning-abilities/)
32. **[Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering](https://md.research.elamur.ai/free/en/papers/tang-2025-unlocking-general-long-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Tang, Xiaolei Wang, Zhihao Lv, et al.*2025 · 19 citations*
33. **[Unveiling Language-Specific Features in Large Language Models via Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/deng-2025-unveiling-language-specific-features-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boyi Deng, Yu Wan, Baosong Yang, et al.*2025 · 18 citations*
34. **[Understanding Jailbreak Success: A Study of Latent Space Dynamics in Large Language Models](https://md.research.elamur.ai/free/en/papers/ball-2026-understanding-jailbreak-success-study-latent/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sarah Ball, Frauke Kreuter, Nina Panickssery*2026 · 17 citations*
35. **[Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms](https://md.research.elamur.ai/free/en/papers/wang-2025-beyond-prompt-engineering-robust-behavior/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ziwen Xu, Shengyu Mao, et al.*2025 · 14 citations*
36. [**Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models arXiv:2407.15645**Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/he-yueya-2024-psychometric-alignment-capturing-human-knowledge/)
37. **[AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak Defender](https://md.research.elamur.ai/free/en/papers/zhao-2025-adasteer-your-aligned-llm-is/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weixiang Zhao, Jiahe Guo, Yulin Hu, et al.*2025 · 11 citations*
38. **[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*
39. **[Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/li-2025-layer-aware-representation-filtering-purifying/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Li, Lijun Li, Zhenghao Lu, et al.*2025 · 11 citations*
40. **[Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive Scoring](https://md.research.elamur.ai/free/en/papers/hua-2026-rethinking-jailbreak-detection-large-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peichun Hua, Hao Li, Shanghao Shi, et al.*2026 · 10 citations*
41. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
42. **[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*
43. **[Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/singh-2025-exposing-achilles-heel-evaluating-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joykirat Singh, Akshay Nambi, Vibhav Vineet*2025 · 8 citations*
44. [**Cutting Through the Noise: Boosting LLM Performance on Math Word Problems**Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/anantheswaran-2024-cutting-through-noise-boosting-llm/)
45. **[Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs](https://md.research.elamur.ai/free/en/papers/siddique-2026-shifting-perspectives-steering-vectors-robust/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zara Siddique, Irtaza Khalid, Liam Turner, et al.*2026 · 6 citations*
46. **[The Validation Gap: A Mechanistic Analysis of How Language Models Compute Arithmetic but Fail to Validate It](https://md.research.elamur.ai/free/en/papers/bertolazzi-2025-validation-gap-mechanistic-analysis-how/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Leonardo Bertolazzi, Philipp Mondorf, Barbara Plank, et al.*2025 · 6 citations*
47. **[False Sense of Security: Why Probing-based Malicious Input Detection Fails to Generalize](https://md.research.elamur.ai/free/en/papers/wang-2026-false-sense-security-why-probing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Wang, Zeming Wei, Qin Liu, et al.*2026 · 5 citations*
48. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
49. [**Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv:2605.11887**Boyi Deng, Xu Wang, Yaoning Wang, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deng-2026-qwen-scope-turning-sparse/)
50. **[Steering Large Language Models for Machine Translation Personalization](https://md.research.elamur.ai/free/en/papers/scalena-2026-steering-large-language-models-machine/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniel Scalena, Gabriele Sarti, Arianna Bisazza, et al.*2026 · 3 citations*
51. **[Universal Jailbreak Suffixes Are Strong Attention Hijackers](https://md.research.elamur.ai/free/en/papers/tov-2026-universal-jailbreak-suffixes-are-strong/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Matan Ben-Tov, Mor Geva, Mahmood Sharif*2026 · 3 citations*
52. **[In-Context Representation Hijacking](https://md.research.elamur.ai/free/en/papers/yona-2026-context-representation-hijacking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Itay Yona, Amir Sarid, Michael Karasik, et al.*2026 · 2 citations*
53. **[Latent Agents: A Post-Training Procedure for Internalized Multi-Agent Debate](https://md.research.elamur.ai/free/en/papers/yi-2026-latent-agents-post-training-procedure/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Seon Keun Yi, Aaron Mueller, Dokyun Lee*2026 · 2 citations*
54. **[Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework](https://md.research.elamur.ai/free/en/papers/weng-2026-safe-sail-fine-grained-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Weng, Han Zheng, Hanyu Zhang, et al.*2026 · 2 citations*
55. **[The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMs](https://md.research.elamur.ai/free/en/papers/mahmoud-2026-unintended-trade-off-ai-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Mahmoud, Ali Khalil, Thommen George Karimpanal, et al.*2026 · 2 citations*
56. **[Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors](https://md.research.elamur.ai/free/en/papers/yin-2026-compiling-activation-steering-into-weights/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Yin, Tianxu Han, Naen Xu, et al.*2026 · 1 citation*
57. **[Deciphering Cultural Representations in Large Language Models via Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zou-2026-deciphering-cultural-representations-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenye Zou, Difan Jiao, Lijie Hu*2026 · 1 citation*
58. [**Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles arXiv:2604.21152**Irti Haq, Belen Saldias*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/haq-2026-dialect-vs-demographics-quantifying-llm/)
59. **[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://md.research.elamur.ai/free/en/papers/ostermann-2026-weights-activations-is-steering-next/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, et al.*2026 · 1 citation*
60. **[In-Distribution Steering: Balancing Control and Coherence in Language Model Generation](https://md.research.elamur.ai/free/en/papers/vogels-2026-distribution-steering-balancing-control-coherence/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Arthur Vogels, Benjamin Wong, Yann Choho, et al.*2026 · 1 citation*
61. **[Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-representation-interventions-enable-lifelong-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuyuan Liu, Shengyu Chen, Xinshuai Dong, et al.*2026 · 1 citation*
62. **[SafeConstellations: Mitigating Over-Refusals in LLMs Through Task-Aware Representation Steering](https://md.research.elamur.ai/free/en/papers/maskey-2026-safeconstellations-mitigating-over-refusals-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Utsav Maskey, Sumit Yadav, Mark Dras, et al.*2026 · 1 citation*
63. [**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/)
64. **[A Simple and Efficient Learning-Style Prompting for LLM Jailbreaking](https://md.research.elamur.ai/free/en/papers/luo-2026-simple-efficient-learning-style-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Yue Wang, Zefeng He, et al.*2026*
65. **[Activation Decomposition and Steering for LLM Backdoor Remediation](https://md.research.elamur.ai/free/en/papers/zhong-2026-activation-decomposition-steering-llm-backdoor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingfeng Zhong, Qiongkai Xu, Usman Naseem*2026*
66. **[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*
67. [**Arabic Safety Alignment as Selective Refusal: An Empirical Study of SFT, DPO, and Guard Calibration arXiv:2608.29378**Mohamad Zbib, Ammar Mohanna*2026*](https://md.research.elamur.ai/free/en/papers/zbib-2026-arabic-safety-alignment-selective-refusal/)
68. **[Calibrating Inference Time Alignment with Sequence-level Risk Accumulation](https://md.research.elamur.ai/free/en/papers/tan-2026-calibrating-inference-time-alignment-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shanwen Tan, Ziyang Dong, Wei Ju, et al.*2026*
69. **[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*
70. **[Defeating Cerberus: Privacy-Leakage Mitigation in Vision Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-defeating-cerberus-privacy-leakage-mitigation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Boyang Zhang, Istemi Ekin Akkus, Ruichuan Chen, et al.*2026*
71. **[Detecting What Queries Seek: Steering LLM Safety with FFN Output Activation Monitoring](https://md.research.elamur.ai/free/en/papers/luo-2026-detecting-what-queries-seek-steering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaohao Luo, Ying Wei, Rui Zhao*2026*
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75. **[From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?](https://md.research.elamur.ai/free/en/papers/mueller-2026-isolation-entanglement-when-do-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aaron Mueller, Andrew Lee, Shruti Joshi, et al.*2026*
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79. **[LLM-VA: Resolving the Jailbreak-Overrefusal Trade-off via Vector Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-llm-va-resolving-jailbreak-overrefusal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Zhang, Dongxia Wang, Yi Liu, et al.*2026*
80. [**LLMs Silently Correct African American English: Auditing and Mitigating Dialect Bias via Activation Steering arXiv:2607.06845**Huan Wu, Ali Emami, Muhammad Furquan Hassan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wu-2026-llms-silently-correct-african-american/)
81. **[Mapping the Circumplex of Affect: Geometric Analysis of Emotion Representations via Hyperspherical Contrastive Learning](https://md.research.elamur.ai/free/en/papers/yamauchi-2026-mapping-circumplex-affect-geometric-analysis/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yusuke Yamauchi, Akiko Aizawa*2026*
82. **[Mechanistic Insights into Deferred Semantic Drift in LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2026-mechanistic-insights-into-deferred-semantic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingjie Zeng, Huayang Li, Liang Yang, et al.*2026*
83. **[Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zheng-2026-model-directions-not-words-mechanistic/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Carolina Zheng, Nicolas Beltran-Velez, Sweta Karlekar, et al.*2026*
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90. **[Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/schaffelder-2026-synthetic-eggs-many-baskets-impact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Max Schaffelder, Albert Gatt*2026*
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93. **[When Correct Beliefs Collapse: Epistemic Resilience of LLMs under Clinical Pressure](https://md.research.elamur.ai/free/en/papers/xiao-2026-when-correct-beliefs-collapse-epistemic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boyu Xiao, Xiuqi Tian, Xuwen Song, et al.*2026*
94. **[When Efficiency Meets Safety: A Benchmark Security Analysis of KV Cache Compression in Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-when-efficiency-meets-safety-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoxiao Ma, Kuofeng Gao, Zeyi Lu, et al.*2026*
95. **[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*

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