---
title: "Who cites Shuyue Stella Li — 262 papers of our library"
description: "262 papers of the Elamur Research library cite the works of Shuyue Stella Li, found in their bibliographies; the most cited first."
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---
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# Who cites Shuyue Stella Li

267 citations of their works from 262 papers of our library (of the 149,439 whose bibliographies we read) · 79 with a page here, the most cited first · [← Shuyue Stella Li](https://md.research.elamur.ai/free/en/authors/shuyue-stella-li/)

1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
2. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
3. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
4. **[TTRL: Test-Time Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zuo-2025-ttrl-test-time-reinforcement-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.*2025 · 76 citations*
5. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
6. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
7. [**Reasoning with Exploration: An Entropy Perspective arXiv:2506.14758**Daixuan Cheng, Shaohan Huang, Xuekai Zhu, et al.*2025 · 63 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2025-reasoning-exploration-entropy-perspective/)
8. **[WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wei-2025-webagent-r1-training-web-agents/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhepei Wei, Wenlin Yao, Yao Liu, et al.*2025 · 36 citations*
9. [**DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research arXiv:2511.19399**Rulin Shao, Akari Asai, Shannon Zejiang Shen, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-dr-tulu-reinforcement-learning-evolving/)
10. [**Baichuan-M1: Pushing the Medical Capability of Large Language Models arXiv:2502.12671**Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)
11. **[Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening](https://md.research.elamur.ai/free/en/papers/he-2025-rewarding-unlikely-lifting-grpo-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andre Wang He, Daniel Fried, Sean Welleck*2025 · 15 citations*
12. **[Ask Patients with Patience: Enabling LLMs for Human-Centric Medical Dialogue with Grounded Reasoning](https://md.research.elamur.ai/free/en/papers/zhu-2025-ask-patients-patience-enabling-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiayuan Zhu, Jiazhen Pan, Yuyuan Liu, et al.*2025 · 10 citations*
13. **[ChatBench: From Static Benchmarks to Human-AI Evaluation](https://md.research.elamur.ai/free/en/papers/chang-2025-chatbench-static-benchmarks-human-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Serina Chang, Ashton Anderson, Jake M. Hofman*2025 · 9 citations*
14. **[A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding](https://md.research.elamur.ai/free/en/papers/selamet-2026-parallel-cross-lingual-benchmark-multimodal/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dilara Torunoğlu-Selamet, Doğukan Arslan, Rodrigo Wilkens, et al.*2026 · 8 citations*
15. **[Localized Cultural Knowledge is Conserved and Controllable in Large Language Models](https://md.research.elamur.ai/free/en/papers/veselovsky-2026-localized-cultural-knowledge-is-conserved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.*2026 · 7 citations*
16. **[Scaling Collaborative Effort with Agents](https://md.research.elamur.ai/free/en/papers/shen-2026-scaling-collaborative-effort-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shannon Zejiang Shen, Valerie Chen, Ken Gu, et al.*2026 · 7 citations*
17. [**Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions arXiv:2504.11373**Wang Bill Zhu, Tianqi Chen, Xinyan Velocity Yu, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-cancer-myth-evaluating-large-language/)
18. [**Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought arXiv:2510.04230**Guijin Son, Donghun Yang, Hitesh Laxmichand Patel, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/son-2025-pushing-multilingual-reasoning-models-language/)
19. **[From Scores to Steps: Diagnosing and Improving LLM Performance in Evidence-Based Medical Calculations](https://md.research.elamur.ai/free/en/papers/wang-2025-scores-steps-diagnosing-improving-llm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Benlu Wang, Iris Xia, Yifan Zhang, et al.*2025 · 5 citations*
20. **[ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs](https://md.research.elamur.ai/free/en/papers/ding-2026-promed-shapley-information-gain-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongxin Ding, Baixiang Huang, Yue Fang, et al.*2026 · 4 citations*
21. **[Better LLM Reasoning via Dual-Play](https://md.research.elamur.ai/free/en/papers/zhang-2026-better-llm-reasoning-dual-play/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Aochong Oliver Li, et al.*2026 · 3 citations*
22. **[Confidence Should Be Calibrated More Than One Turn Deep](https://md.research.elamur.ai/free/en/papers/zhang-2026-confidence-should-be-calibrated-more/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Chengzhengxu Li, Xiaoming Liu, et al.*2026 · 3 citations*
23. **[LeCoDe: A Benchmark Dataset for Interactive Legal Consultation Dialogue Evaluation](https://md.research.elamur.ai/free/en/papers/yuan-2026-lecode-benchmark-dataset-interactive-legal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weikang Yuan, Kaisong Song, Zhuoren Jiang, et al.*2026 · 3 citations*
24. **[Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-mitigating-catastrophic-forgetting-target-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, et al.*2026 · 3 citations*
25. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
26. **[Abstain-R1: Calibrated Abstention and Post-Refusal Clarification via Verifiable RL](https://md.research.elamur.ai/free/en/papers/zhai-2026-abstain-r1-calibrated-abstention-post/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haotian Zhai, Jingcheng Liang, Dongyeop Kang*2026 · 2 citations*
27. **[BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-blend-vis-benchmarking-multimodal-cultural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bryan Chen Zhengyu Tan, Weihua Zheng, Zhengyuan Liu, et al.*2026 · 2 citations*
28. **[Gained in Translation: Privileged Pairwise Judges Enhance Multilingual Reasoning](https://md.research.elamur.ai/free/en/papers/sutawika-2026-gained-translation-privileged-pairwise-judges/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lintang Sutawika, Gokul Swamy, Steven Wu, et al.*2026 · 2 citations*
29. **[RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models](https://md.research.elamur.ai/free/en/papers/muhamed-2026-refusalbench-generative-evaluation-selective-refusal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aashiq Muhamed, Leonardo F. R. Ribeiro, Markus Dreyer, et al.*2026 · 2 citations*
30. **[The olmOCR Project: Building Fully Open OCR using VLMs](https://md.research.elamur.ai/free/en/papers/poznanski-2026-olmocr-project-building-fully-open/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jake Poznanski, Kyle Lo, Luca Soldaini*2026 · 2 citations*
31. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation*
32. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
33. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation*
34. **[Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-leaderboard-rethinking-medical-benchmarks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Wang, Zizhan Ma, Guo Yu, et al.*2026 · 1 citation*
35. **[BSC's Submission to the Instruction Following Track of IWSLT 2026](https://md.research.elamur.ai/free/en/papers/pareras-2026-bsc-s-submission-instruction-following/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Oriol Pareras, Joan Llado, Pol Buitrago, et al.*2026 · 1 citation*
36. **[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*
37. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation*
38. **[From Interpretability to Performance: Optimizing Retrieval Heads for Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-interpretability-performance-optimizing-retrieval-heads/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Youmi Ma, Naoaki Okazaki*2026 · 1 citation*
39. **[IS-CoT: Breaking the Long-form Generation Collapse via Interleaved Structural Thinking](https://md.research.elamur.ai/free/en/papers/sun-2026-is-cot-breaking-long-form/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zechen Sun, Yuyang Sun, Zecheng Tang, et al.*2026 · 1 citation*
40. [**KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full Report arXiv:2606.03773**Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kraus-2026-klettermix-climbing-toward-high-quality/)
41. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation*
42. **[No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding](https://md.research.elamur.ai/free/en/papers/permadi-2026-no-shortcuts-culture-indonesian-multi/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi, et al.*2026 · 1 citation*
43. **[OLA: Output Language Alignment in Code-Switched LLM Interactions](https://md.research.elamur.ai/free/en/papers/oh-2026-ola-output-language-alignment-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Juhyun Oh, Haneul Yoo, Faiz Ghifari Haznitrama, et al.*2026 · 1 citation*
44. **[Prior Beliefs Prejudice LLM-as-Judge: Evidence from Persuasion Evaluation](https://md.research.elamur.ai/free/en/papers/zahraei-2026-prior-beliefs-prejudice-llm-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pardis Sadat Zahraei, Xiaoning Wang, Nimet Beyza Bozdag, et al.*2026 · 1 citation*
45. **[Ready to Translate, Not to Represent? Bias and Performance Gaps in Multilingual LLMs Across Language Families and Domains](https://md.research.elamur.ai/free/en/papers/sayeedi-2026-ready-translate-not-represent-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md. Faiyaz Abdullah Sayeedi, Subhey Sadi Rahman, Md. Mahbub Alam, et al.*2026 · 1 citation*
46. **[Reasoning Up the Instruction Ladder for Controllable Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-reasoning-up-instruction-ladder-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.*2026 · 1 citation*
47. **[Strong Reasoning Isn't Enough: Evaluating Evidence Elicitation in Interactive Diagnosis](https://md.research.elamur.ai/free/en/papers/long-2026-strong-reasoning-isn-t-enough/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuohan Long, Zhongyu Wei*2026 · 1 citation*
48. **[Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models](https://md.research.elamur.ai/free/en/papers/mammen-2026-who-endorsed-it-measuring-authority/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Priyanka Mary Mammen, Emil Joswin, Shankar Venkitachalam*2026 · 1 citation*
49. **[x1: Learning to Think Adaptively Across Languages and Cultures](https://md.research.elamur.ai/free/en/papers/ye-2026-x1-learning-think-adaptively-across/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangfan Ye, Xiaocheng Feng, Xiachong Feng, et al.*2026 · 1 citation*
50. **[CultranAI at PalmX 2025: Data Augmentation for Cultural Knowledge Representation](https://md.research.elamur.ai/free/en/papers/bhatti-2025-cultranai-palmx-2025-data-augmentation/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Hunzalah Hassan Bhatti, Youssef Ahmed, Md Arid Hasan, et al.*2025 · 1 citation*
51. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
52. **[AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages](https://md.research.elamur.ai/free/en/papers/yu-2026-afriquellm-how-data-mixing-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Yu, Tianyi Xu, Michael A. Hedderich, et al.*2026*
53. **[AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?](https://md.research.elamur.ai/free/en/papers/sun-2026-algbench-what-extent-do-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Henan Sun, Kaichi Yu, Yuyao Wang, et al.*2026*
54. **[Boosting Self-Consistency with Ranking](https://md.research.elamur.ai/free/en/papers/marina-2026-boosting-self-consistency-ranking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maria Marina, Daniil Moskovskiy, Sergey Pletenev, et al.*2026*
55. **[Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical Reasoning](https://md.research.elamur.ai/free/en/papers/merenda-2026-can-llms-reason-like-doctors/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Flavio Merenda, Jose Manuel Gomez-Perez, German Rigau*2026*
56. **[Common to Whom? Regional Cultural Commonsense and LLM Bias in India](https://md.research.elamur.ai/free/en/papers/madhusudan-2026-common-whom-regional-cultural-commonsense/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sangmitra Madhusudan, Trush Shashank More, Steph Buongiorno, et al.*2026*
57. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026*
58. **[Distributional Alignment for Large Language Models under Domain Shift](https://md.research.elamur.ai/free/en/papers/pham-2026-distributional-alignment-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Thanh Pham, Lizhen Qu, Zhuang Li, et al.*2026*
59. **[Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-distributional-clarity-hidden-driver-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoning Sun, Mingzhu Cai, Huang He, et al.*2026*
60. [**Don't ‘Well, Actually' Me Unless You Know What You're Talking About: Weak Presupposition Verification Degrades General QA Performance arXiv:2608.06539**Shenran Wang, Vered Shwartz, Hila Gonen*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-well-actually-me/)
61. **[Experience is the Teacher: Reusing Atomic Thoughts from LLMs to Improve Medical Dialogue](https://md.research.elamur.ai/free/en/papers/yu-2026-experience-is-teacher-reusing-atomic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangya Yu, Hui Luo, Qi Ye, et al.*2026*
62. **[Exploring Fine-Tuning for In-Context Retrieval and Efficient KV-Caching in Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/molfese-2026-exploring-fine-tuning-context-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Francesco Maria Molfese, Momchil Hardalov, Rexhina Blloshmi, et al.*2026*
63. [**Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning arXiv:2608.18361**Mena Attia, Mona Diab, Thamar Solorio*2026*](https://md.research.elamur.ai/free/en/papers/attia-2026-figurative-cultural-knowledge-llms-investigating/)
64. **[From Narrow Unlearning to Emergent Misalignment in LLMs](https://md.research.elamur.ai/free/en/papers/mushtaq-2026-narrow-unlearning-emergent-misalignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna, et al.*2026*
65. **[Heterogeneity in Formal Linguistic Competence of Language Models: Is Data the Real Bottleneck?](https://md.research.elamur.ai/free/en/papers/renduchintala-2026-heterogeneity-formal-linguistic-competence-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**H S V N S Kowndinya Renduchintala, Sumit Bhatia*2026*
66. **[KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?](https://md.research.elamur.ai/free/en/papers/saha-2026-kismath-do-llms-have-knowledge/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Soumadeep Saha, Akshay Chaturvedi, Saptarshi Saha, et al.*2026*
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