---
title: "Who cites Heng Huang — 272 papers of our library"
description: "272 papers of the Elamur Research library cite the works of Heng Huang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/heng-huang/cited-by/"
---
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# Who cites Heng Huang

276 citations of their works from 272 papers of our library (of the 149,439 whose bibliographies we read) · 73 with a page here, the most cited first · [← Heng Huang](https://md.research.elamur.ai/free/en/authors/heng-huang/)

1. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,974 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. [**BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation arXiv:2201.12086**Junnan Li, Dongxu Li, Caiming Xiong, et al.*2022 · 1,523 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-blip-bootstrapping-language-image-pre/)
4. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
5. **[HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 335 citations*
6. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
7. **[On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 237 citations*
8. **[Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 207 citations*
9. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/)
10. [**LESS: Selecting Influential Data for Targeted Instruction Tuning arXiv:2402.04333**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 178 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/)
11. [**What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning arXiv:2312.15685**Wei Liu, Weihao Zeng, Keqing He, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-makes-good-data-alignment-comprehensive/)
12. [**OpenChat: Advancing Open-source Language Models with Mixed-Quality Data arXiv:2309.11235**Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-openchat-advancing-open-source-language/)
13. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning arXiv:2308.12032**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
14. **[Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/wang-2024-interpretable-preferences-multi-objective-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoxiang Wang, Wei Xiong, Tengyang Xie, et al.*2024 · 153 citations*
15. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning arXiv:2312.01552**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
16. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing arXiv:2406.08464**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
17. [**Self-Alignment with Instruction Backtranslation arXiv:2308.06259**Xian Li, Ping Yu, Chunting Zhou, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-self-alignment-instruction-backtranslation/)
18. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
19. **[Survey of Cultural Awareness in Language Models: Text and Beyond](https://md.research.elamur.ai/free/en/papers/pawar-2025-survey-cultural-awareness-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Siddhesh Pawar, Junyeong Park, Jiho Jin, et al.*2025 · 106 citations*
20. **[Disentangling Length from Quality in Direct Preference Optimization](https://md.research.elamur.ai/free/en/papers/park-2024-disentangling-length-quality-direct-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ryan Park, Rafael Rafailov, Stefano Ermon, et al.*2024 · 105 citations*
21. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
22. **[Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling](https://md.research.elamur.ai/free/en/papers/maini-2024-rephrasing-web-recipe-compute-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratyush Maini, Skyler Seto, Richard Bai, et al.*2024 · 90 citations*
23. **[Reinforcement Learning for Reasoning in Large Language Models with One Training Example](https://md.research.elamur.ai/free/en/papers/wang-2025-reinforcement-learning-reasoning-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yiping Wang, Qing Yang, Zhiyuan Zeng, et al.*2025 · 87 citations*
24. [**Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving arXiv:2502.07640**Yong Lin, Shange Tang, Bohan Lyu, et al.*2025 · 84 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-goedel-prover-frontier-model-open/)
25. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
26. [**DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving arXiv:2407.13690**Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-dart-math-difficulty-aware-rejection/)
27. [**Instruction Mining: Instruction Data Selection for Tuning Large Language Models arXiv:2307.06290**Yihan Cao, Yanbin Kang, Chi Wang, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-instruction-mining-instruction-data-selection/)
28. [**Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains arXiv:2507.17746**Anisha Gunjal, Anthony Wang, Elaine Lau, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/gunjal-2025-rubrics-rewards-reinforcement-learning-verifiable/)
29. **[Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards](https://md.research.elamur.ai/free/en/papers/wang-2024-arithmetic-control-llms-diverse-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Wang, Yong Lin, Wei Xiong, et al.*2024 · 68 citations*
30. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
31. **[One-Shot Learning as Instruction Data Prospector for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-one-shot-learning-as-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunshui Li, Binyuan Hui, Xiaobo Xia, et al.*2024 · 61 citations*
32. [**Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning arXiv:2402.00530**Ming Li, Yong Zhang, Shwai He, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-superfiltering-weak-strong-data-filtering/)
33. [**ODIN: Disentangled Reward Mitigates Hacking in RLHF arXiv:2402.07319**Lichang Chen, Chen Zhu, Davit Soselia, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-odin-disentangled-reward-mitigates-hacking/)
34. [**SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models arXiv:2504.11468**Hardy Chen, Haoqin Tu, Fali Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-sft-rl-early-investigation-training/)
35. **[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*
36. [**DsDm: Model-Aware Dataset Selection with Datamodels arXiv:2401.12926**Logan Engstrom, Axel Feldmann, Aleksander Madry*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/engstrom-2024-dsdm-model-aware-dataset-selection/)
37. **[PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2024-plug-leveraging-pivot-language-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihan Zhang, Dong-Ho Lee, Yuwei Fang, et al.*2024 · 28 citations*
38. **[Following Length Constraints in Instructions](https://md.research.elamur.ai/free/en/papers/yuan-2025-following-length-constraints-instructions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weizhe Yuan, Ilia Kulikov, Ping Yu, et al.*2025 · 22 citations*
39. [**Entropy Law: The Story Behind Data Compression and LLM Performance arXiv:2407.06645**Mingjia Yin, Chuhan Wu, Yufei Wang, et al.*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/yin-2024-entropy-law-story-behind-data/)
40. **[CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation](https://md.research.elamur.ai/free/en/papers/ziegler-2025-craft-your-dataset-task-specific/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.*2025 · 20 citations*
41. **[MinT: Boosting Generalization in Mathematical Reasoning via Multi-view Fine-tuning](https://md.research.elamur.ai/free/en/papers/liang-2024-mint-boosting-generalization-mathematical-reasoning/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhenwen Liang, Dian Yu, Xiaoman Pan, et al.*2024 · 19 citations*
42. [**Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models arXiv:2412.02980**Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-surveying-effects-quality-diversity-complexity/)
43. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
44. **[JuStRank: Benchmarking LLM Judges for System Ranking](https://md.research.elamur.ai/free/en/papers/gera-2025-justrank-benchmarking-llm-judges-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ariel Gera, Odellia Boni, Yotam Perlitz, et al.*2025 · 15 citations*
45. **[A Survey on Efficient Large Language Model Training: From Data-centric Perspectives](https://md.research.elamur.ai/free/en/papers/luo-2025-survey-efficient-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyu Luo, Bohan Wu, Xiao Luo, et al.*2025 · 14 citations*
46. **[Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering](https://md.research.elamur.ai/free/en/papers/si-2025-aligning-large-language-models-follow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 11 citations*
47. **[Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric](https://md.research.elamur.ai/free/en/papers/yang-2025-measuring-data-diversity-instruction-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Yang Nan, Junjie Ye, et al.*2025 · 11 citations*
48. [**Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks arXiv:2602.05125**William F. Shen, Xinchi Qiu, Chenxi Whitehouse, et al.*2026 · 9 citations*](https://md.research.elamur.ai/free/en/papers/shen-2026-rethinking-rubric-generation-improving-llm/)
49. **[Nudging: Inference-time Alignment of LLMs via Guided Decoding](https://md.research.elamur.ai/free/en/papers/fei-2025-nudging-inference-time-alignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Fei, Yasaman Razeghi, Sameer Singh*2025 · 8 citations*
50. **[Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm](https://md.research.elamur.ai/free/en/papers/li-2025-add-one-incremental-sample-selection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhuo Li, Yuhao Du, Xiaoqi Jiao, et al.*2025 · 5 citations*
51. **[GATEAU: Selecting Influential Samples for Long Context Alignment](https://md.research.elamur.ai/free/en/papers/si-2025-gateau-selecting-influential-samples-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuzheng Si, Haozhe Zhao, Gang Chen, et al.*2025 · 5 citations*
52. [**Baichuan Alignment Technical Report arXiv:2410.14940**Mingan Lin, Fan Yang, Yanjun Shen, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-baichuan-alignment-technical-report/)
53. **[Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-select2reason-efficient-instruction-tuning-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cehao Yang, Xueyuan Lin, Xiaojun Wu, et al.*2026 · 4 citations*
54. **[MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis](https://md.research.elamur.ai/free/en/papers/yu-2026-mathagent-adversarial-evolution-constraint-graphs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zixiong Yu, Jun Rao, Guhan Chen, et al.*2026 · 3 citations*
55. **[Aligning Large Language Models via Fully Self-Synthetic Data](https://md.research.elamur.ai/free/en/papers/yin-2026-aligning-large-language-models-fully/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangjian Yin, Zhepei Wei, Xinyu Zhu, et al.*2026 · 2 citations*
56. **[Bias Fitting to Mitigate Length Bias of Reward Model in RLHF](https://md.research.elamur.ai/free/en/papers/zhao-2026-bias-fitting-mitigate-length-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kangwen Zhao, Jianfeng Cai, Jinhua Zhu, et al.*2026 · 2 citations*
57. [**Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety**Qian Shen, Fanghua Cao, Min Yao, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shen-2026-children-s-english-reading-story/)
58. **[HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive Content](https://md.research.elamur.ai/free/en/papers/vecchi-2026-harm-learning-hate-aware-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.*2026 · 1 citation*
59. **[CypherSmith: Transforming Text-to-Cypher Generation for LLMs with Synthetic Data](https://md.research.elamur.ai/free/en/papers/zhang-2026-cyphersmith-transforming-text-cypher-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeyu Zhang, Kexuan Sun, Zheng Tang, et al.*2026*
60. **[Data-Efficient Adaptation to Contextual Shifts in LLM-based Conversational Recommendation](https://md.research.elamur.ai/free/en/papers/yang-2026-data-efficient-adaptation-contextual-shifts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hyeongjun Yang, Donghyun Kim, Seokju Hwang, et al.*2026*
61. **[Debiasing Reward Models via Causally Motivated Inference-Time Intervention](https://md.research.elamur.ai/free/en/papers/shinoda-2026-debiasing-reward-models-causally-motivated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida*2026*
62. **[From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-insight-action-novel-framework-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ling Shi, Xinwei Wu, Xiaohu Zhao, et al.*2026*
63. **[GROKE: Vision-Free Navigation Instruction Evaluation via Graph Reasoning on OpenStreetMap](https://md.research.elamur.ai/free/en/papers/shami-2026-groke-vision-free-navigation-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Farzad Shami, Subhrasankha Dey, Nico Van de Weghe, et al.*2026*
64. **[InstructDiff: Domain-Adaptive Data Selection via Contrastive Entropy for Efficient LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/su-2026-instructdiff-domain-adaptive-data-selection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyou Su, He Zhu, Xiao Luo, et al.*2026*
65. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026*
66. **[LaCoMSA: Language-Consistency Multilingual Self-Alignment with Latent Representation Rewarding](https://md.research.elamur.ai/free/en/papers/tran-2026-lacomsa-language-consistency-multilingual-self/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Khanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen*2026*
67. **[Layer-aware Dual-directional Modulation for Low-resource Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2026-layer-aware-dual-directional-modulation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Siqi Zhang, Ran Song, Shuting Jiang, et al.*2026*
68. **[Parallel Corpus Filtering Based on Semantic Similarity and Surface Dissimilarity for Japanese Text Simplification with LLMs](https://md.research.elamur.ai/free/en/papers/maekawa-2026-parallel-corpus-filtering-based-semantic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daisuke Maekawa, Tomoyuki Kajiwara, Takashi Ninomiya*2026*
69. **[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*
70. **[Synthetic Data Generation for Training Diversified Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-synthetic-data-generation-training-diversified/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianhui Zhang, Bei Peng, Danushka Bollegala*2026*
71. **[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*
72. **[WildReward: Learning Reward Models from In-the-Wild Human Interactions](https://md.research.elamur.ai/free/en/papers/peng-2026-wildreward-learning-reward-models-wild/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2026*
73. [**SmolKalam: Ensemble Quality-Filtered Translation at Scale for High Quality Arabic Post-Training Data arXiv:2511.18411**Sultan Alrashed, Chadi Helwe, Francesco Orabona*2025*](https://md.research.elamur.ai/free/en/papers/alrashed-2025-smolkalam-ensemble-quality-filtered-translation/)

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