---
title: "Who cites Yike Guo — 299 papers of our library"
description: "299 papers of the Elamur Research library cite the works of Yike Guo, found in their bibliographies; the most cited first."
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---
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# Who cites Yike Guo

310 citations of their works from 299 papers of our library (of the 149,439 whose bibliographies we read) · 89 with a page here, the most cited first · [← Yike Guo](https://md.research.elamur.ai/free/en/authors/yike-guo/)

1. **[Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach](https://md.research.elamur.ai/free/en/papers/yin-2019-benchmarking-zero-shot-text-classification/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenpeng Yin, Jamaal Hay, Dan Roth*2019 · 735 citations*
2. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
3. [**LightRAG: Simple and Fast Retrieval-Augmented Generation arXiv:2410.05779**Zirui Guo, Lianghao Xia, Yanhua Yu, et al.*2024 · 316 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-lightrag-simple-fast-retrieval-augmented/)
4. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)
5. **[Text Classification Using Label Names Only: A Language Model Self-Training Approach](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*
6. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
7. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
8. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
9. **[CultureLLM: Incorporating Cultural Differences into Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-culturellm-incorporating-cultural-differences-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Cheng Li, Mengzhou Chen, Jindong Wang, et al.*2024 · 162 citations*
10. **[Enhancing Cross-target Stance Detection with Transferable Semantic-Emotion Knowledge](https://md.research.elamur.ai/free/en/papers/zhang-2020-enhancing-cross-target-stance-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowen Zhang, Min Yang, Xutao Li, et al.*2020 · 160 citations*
11. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
12. [**The Alignment Problem from a Deep Learning Perspective arXiv:2209.00626**Richard Ngo, Lawrence Chan, Soren Mindermann*2022 · 121 citations*](https://md.research.elamur.ai/free/en/papers/ngo-2022-alignment-problem-deep-learning-perspective/)
13. [**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/)
14. **[ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/chen-2025-research-learning-reason-search-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mingyang Chen, Linzhuang Sun, Tianpeng Li, et al.*2025 · 99 citations*
15. [**Safety Alignment Should Be Made More Than Just a Few Tokens Deep arXiv:2406.05946**Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-safety-alignment-should-made-more/)
16. **[Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-not-all-countries-celebrate-thanksgiving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Wang, Wenxiang Jiao, Jingyuan Huang, et al.*2024 · 96 citations*
17. **[A Survey of Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/kaufmann-2023-survey-reinforcement-learning-human-feedback/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Timo Kaufmann, Paul Weng, Viktor Bengs, et al.*2023 · 92 citations*
18. [**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/)
19. **[PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference](https://md.research.elamur.ai/free/en/papers/ji-2025-pku-saferlhf-multi-level-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaming Ji, Donghai Hong, Borong Zhang, et al.*2025 · 83 citations*
20. [**FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research arXiv:2405.13576**Jiajie Jin, Yutao Zhu, Guanting Dong, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-flashrag-modular-toolkit-efficient-retrieval/)
21. **[Black-Box Prompt Optimization: Aligning Large Language Models without Model Training](https://md.research.elamur.ai/free/en/papers/cheng-2024-black-box-prompt-optimization-aligning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiale Cheng, Xiao Liu, Kehan Zheng, et al.*2024 · 72 citations*
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. [**OS-Copilot: Towards Generalist Computer Agents with Self-Improvement arXiv:2402.07456**Zhiyong Wu, Chengcheng Han, Zichen Ding, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-os-copilot-towards-generalist-computer/)
24. **[The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm](https://md.research.elamur.ai/free/en/papers/aakanksha-2024-multilingual-alignment-prism-aligning-global/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aakanksha, Arash Ahmadian, Beyza Ermis, et al.*2024 · 49 citations*
25. **[ValueBench: Towards Comprehensively Evaluating Value Orientations and Understanding of Large Language Models](https://md.research.elamur.ai/free/en/papers/ren-2024-valuebench-comprehensively-evaluating-value-orientations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanyi Ren, Haoran Ye, Hanjun Fang, et al.*2024 · 43 citations*
26. [**Qwen3Guard Technical Report arXiv:2510.14276**Haiquan Zhao, Chenhan Yuan, Fei Huang, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-qwen3guard-technical-report/)
27. [**Weaver: Foundation Models for Creative Writing arXiv:2401.17268**Tiannan Wang; Jiamin Chen; Qingrui Jia; Shuai Wang; Ruoyu Fang; Huilin Wang; Zhaowei Gao; Chunzhao Xie; Chuou Xu; Jihong Dai; Yibin Liu; Jialong Wu; Shengwei Ding; Long Li; Zhiwei Huang; Xinle Deng; Teng Yu; Gangan Ma; Han Xiao; Zixin Chen; Danjun Xiang; Yunxia Wang; Yuanyuan Zhu; Yi Xiao; Jing Wang; Yiru Wang; Siran Ding; Jiayang Huang; Jiayi Xu; Yilihamu Tayier; Zhenyu Hu; Yuan Gao; Chengfeng Zheng; Yueshu Ye; Yihang Li; Lei Wan; Xinyue Jiang; Yujie Wang; Siyu Cheng; Zhule Song; Xiangru Tang; Xiaohua Xu; Ningyu Zhang; Huajun Chen; Yuchen Eleanor Jiang;, Wangchunshu Zhou*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-weaver-foundation-models-creative-writing/)
28. **[CIDAR: Culturally Relevant Instruction Dataset For Arabic](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-cidar-culturally-relevant-instruction-dataset/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zaid Alyafeai, Khalid Almubarak, Ahmed Ashraf, et al.*2024 · 30 citations*
29. **[Hierarchical Document Refinement for Long-context Retrieval-augmented Generation](https://md.research.elamur.ai/free/en/papers/jin-2025-hierarchical-document-refinement-long-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Jin, Xiaoxi Li, Guanting Dong, et al.*2025 · 25 citations*
30. **[Aligning LLMs with Individual Preferences via Interaction](https://md.research.elamur.ai/free/en/papers/wu-2025-aligning-llms-individual-preferences-interaction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shujin Wu, Yi R. Fung, Cheng Qian, et al.*2025 · 24 citations*
31. [**Personality Alignment of Large Language Models arXiv:2408.11779**Minjun Zhu, Yixuan Weng, Linyi Yang, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-personality-alignment-large-language-models/)
32. [**MindSearch: Mimicking Human Minds Elicits Deep AI Searcher arXiv:2407.20183**Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mindsearch-mimicking-human-minds-elicits/)
33. **[RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions](https://md.research.elamur.ai/free/en/papers/liu-2025-rag-instruct-boosting-llms-diverse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wanlong Liu, Junying Chen, Ke Ji, et al.*2025 · 19 citations*
34. [**Timo: Towards Better Temporal Reasoning for Language Models arXiv:2406.14192**Zhaochen Su, Jun Zhang, Tong Zhu, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-timo-towards-better-temporal-reasoning/)
35. **[SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement](https://md.research.elamur.ai/free/en/papers/jain-2025-simpledoc-multi-modal-document-understanding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chelsi Jain, Yiran Wu, Yifan Zeng, et al.*2025 · 16 citations*
36. **[MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming](https://md.research.elamur.ai/free/en/papers/guo-2025-mtsa-multi-turn-safety-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Guo, Jing Li, Wenya Wang, et al.*2025 · 14 citations*
37. **[Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas](https://md.research.elamur.ai/free/en/papers/balepur-2025-whose-boat-does-it-float/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Vishakh Padmakumar, Fumeng Yang, et al.*2025 · 12 citations*
38. [**SaRO: Enhancing LLM Safety through Reasoning-based Alignment arXiv:2504.09420**Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/mou-2025-saro-enhancing-llm-safety-through/)
39. **[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*
40. **[DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking](https://md.research.elamur.ai/free/en/papers/li-2025-deepsolution-boosting-complex-engineering-solution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuoqun Li, Haiyang Yu, Xuanang Chen, et al.*2025 · 10 citations*
41. **[RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-richrag-crafting-rich-responses-multi/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shuting Wang, Xin Yu, Mang Wang, et al.*2025 · 10 citations*
42. **[Selective Preference Optimization via Token-Level Reward Function Estimation](https://md.research.elamur.ai/free/en/papers/yang-2025-selective-preference-optimization-token-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kailai Yang, Zhiwei Liu, Qianqian Xie, et al.*2025 · 8 citations*
43. **[MPO: Multilingual Safety Alignment via Reward Gap Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2025-mpo-multilingual-safety-alignment-reward/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weixiang Zhao, Yulin Hu, Yang Deng, et al.*2025 · 7 citations*
44. [**TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation arXiv:2503.04872**Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-tinyr1-32b-preview-boosting-accuracy/)
45. **[FanarGuard: A Culturally-Aware Moderation Filter for Arabic Language Models](https://md.research.elamur.ai/free/en/papers/fatehkia-2026-fanarguard-culturally-aware-moderation-filter/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Masoomali Fatehkia, Enes Altinisik, Husrev Taha Sencar*2026 · 5 citations*
46. **[MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application](https://md.research.elamur.ai/free/en/papers/peng-2026-multifinben-benchmarking-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueqing Peng, Lingfei Qian, Yan Wang, et al.*2026 · 4 citations*
47. **[ARK: Answer-Centric Retriever Tuning via KG-augmented Curriculum Learning](https://md.research.elamur.ai/free/en/papers/zhou-2026-ark-answer-centric-retriever-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Zhou, Hang Ding, Haiyun Jiang*2026 · 3 citations*
48. **[HAUNTATTACK: When Attack Follows Reasoning as a Shadow](https://md.research.elamur.ai/free/en/papers/ma-2026-hauntattack-when-attack-follows-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyuan Ma, Rui Li, Zheng Li, et al.*2026 · 3 citations*
49. **[Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward Models](https://md.research.elamur.ai/free/en/papers/wang-2026-outcome-accuracy-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binghai Wang, Yantao Liu, Yuxuan Liu, et al.*2026 · 3 citations*
50. **[Perception, Understanding and Reasoning: A Multimodal Benchmark for Video Fake News Detection](https://md.research.elamur.ai/free/en/papers/yakun-2026-perception-understanding-reasoning-multimodal-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cui Yakun, Peng Qi, Fushuo Huo, et al.*2026 · 3 citations*
51. **[ReflectiveRAG: Rethinking Adaptivity in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/verma-2026-reflectiverag-rethinking-adaptivity-retrieval-augmented/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Akshay Verma, Swapnil Gupta, Siddharth Pillai, et al.*2026 · 3 citations*
52. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
53. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
54. **[Context-attended Adversarial Reinforcement Learning for Robust Multi-step Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/ren-2026-context-attended-adversarial-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingtao Ren, Xiao Luo, Yu-Cheng Chang, et al.*2026 · 1 citation*
55. **[FinCall-Surprise: A Large Scale Multi-modal Benchmark for Earning Surprise Prediction](https://md.research.elamur.ai/free/en/papers/shu-2026-fincall-surprise-large-scale-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dong Shu, Yanguang Liu, Huopu Zhang, et al.*2026 · 1 citation*
56. **[MemoBrain: Executive Memory as an Agentic Brain for Reasoning](https://md.research.elamur.ai/free/en/papers/qian-2026-memobrain-executive-memory-as-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongjin Qian, Zhao Cao, Zheng Liu*2026 · 1 citation*
57. **[MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/liu-2026-mtmcs-bench-evaluating-contextual-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Dongwhi Kim, Yixin Wan, et al.*2026 · 1 citation*
58. **[Towards Proactive Personalization through Profile Customization for Individual Users in Dialogues](https://md.research.elamur.ai/free/en/papers/zhang-2026-proactive-personalization-through-profile-customization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaotian Zhang, Yuan Wang, Ruizhe Chen, et al.*2026 · 1 citation*
59. **[Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection](https://md.research.elamur.ai/free/en/papers/tan-2026-understanding-structured-financial-data-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuwei Tan, Yao Ma, Xueru Zhang*2026 · 1 citation*
60. **[When Do Large Language Models Exhibit Unsolicited Deception?](https://md.research.elamur.ai/free/en/papers/taylor-2026-when-do-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Samuel M. Taylor, Benjamin K. Bergen*2026 · 1 citation*
61. [**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/)
62. **[Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data Pipelines](https://md.research.elamur.ai/free/en/papers/song-2026-alignment-tuning-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hwanjun Song*2026*
63. **[Communication-Efficient Desire Alignment for Proactive Embodied Human–Agent Interaction](https://md.research.elamur.ai/free/en/papers/wang-2026-communication-efficient-desire-alignment-proactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanfei Wang, Xinju Huang, Fangwei Zhong, et al.*2026*
64. **[Context-Value-Action Architecture for Value-Driven Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhang-2026-context-value-action-architecture-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**TianZe Zhang, Sirui Sun, Yuhang Xie, et al.*2026*
65. **[DataArc-SynData-Toolkit: A Unified Closed-Loop Framework for Multi-Path, Multimodal, and Multilingual Data Synthesis](https://md.research.elamur.ai/free/en/papers/shi-2026-dataarc-syndata-toolkit-unified-closed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhichao Shi, Cehao Yang, Hao Zhou, et al.*2026*
66. **[DialogGuard: Multi-Agent Psychosocial Safety Evaluation Interface of Sensitive LLM Responses](https://md.research.elamur.ai/free/en/papers/luo-2026-dialogguard-multi-agent-psychosocial-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Luo, Guy Laban*2026*
67. **[FinMRAGBench: A Realistic and Complex Benchmark for Multi-Modal RAG in Financial Document Analysis](https://md.research.elamur.ai/free/en/papers/yang-2026-finmragbench-realistic-complex-benchmark-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shouqing Yang, Qi Zhang, Yuhang Yang, et al.*2026*
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69. [**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/)
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72. **[KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-knowledgeberg-evaluating-systematic-knowledge-coverage/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Zhang, Qianru Meng, Yongjian Chen, et al.*2026*
73. **[LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety](https://md.research.elamur.ai/free/en/papers/yang-2026-lasa-language-agnostic-semantic-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junxiao Yang, Haoran Liu, Jinzhe Tu, et al.*2026*
74. **[MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/xiao-2026-mass-rag-multi-agent-synthesis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingchen Xiao, Heyan Huang, Runheng Liu, et al.*2026*
75. **[NEST: Nested Evidence Survival for Retrieval](https://md.research.elamur.ai/free/en/papers/verma-2026-nest-nested-evidence-survival-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akshay Verma, Siddharth Pillai, Prateek Sircar, et al.*2026*
76. **[NP-Hard Lower Bound Complexity for Semantic Self-Verification](https://md.research.elamur.ai/free/en/papers/young-2026-np-hard-lower-bound-complexity/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Robin Young*2026*
77. [**Polite but Misaligned: Evaluating LLM Politeness Judgments Against Human Pragmatic Norms EMNLP2026**Rong Wang; Kun Sun;, Yadong Guo*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-polite-but-misaligned-evaluating-llm/)
78. **[Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs](https://md.research.elamur.ai/free/en/papers/si-2026-pruning-unsafe-tickets-resource-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wai Man Si, Mingjie Li, Michael Backes, et al.*2026*
79. **[RADO: Reasoning Audit-Driven Optimization for Rigorous Reasoning in High-Stakes Domains](https://md.research.elamur.ai/free/en/papers/tan-2026-rado-reasoning-audit-driven-optimization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijie Tan, Xu Chu, Guanyu Wang, et al.*2026*
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83. **[Structure Guided Retrieval-Augmented Generation for Factual Queries](https://md.research.elamur.ai/free/en/papers/xie-2026-structure-guided-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miao Xie, Xiao Zhang, Yi Li, et al.*2026*
84. **[Test-Time Strategies for More Efficient and Accurate Agentic RAG](https://md.research.elamur.ai/free/en/papers/sharma-2026-test-time-strategies-more-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abhinav Sharma, Brian Zhang, Deepti Guntur, et al.*2026*
85. **[The Structure-Content Trade-off in Knowledge Graph Retrieval: A Diagnostic Study of Question Decomposition](https://md.research.elamur.ai/free/en/papers/six-2026-structure-content-trade-off-knowledge/) [Knowledge Graphs and Large Language Models Workshop (KG-LLM) @ LREC26](https://md.research.elamur.ai/free/en/venues/kallm/)**Valentin Six, Gaël de Chalendar, Evan Dufraisse*2026*
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87. **[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*
88. **[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*
89. **[Survey on Application of Retrieval-augmented Generation in Software Engineering (检索增强生成在软件工程中的应用综述)](https://md.research.elamur.ai/free/en/papers/zhang-2025-application-retrieval-augmented/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Quanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.*2025*

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