---
title: "Who cites Jiahui Geng — 210 papers of our library"
description: "210 papers of the Elamur Research library cite the works of Jiahui Geng, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jiahui-geng/cited-by/"
---
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# Who cites Jiahui Geng

211 citations of their works from 210 papers of our library (of the 149,439 whose bibliographies we read) · 60 with a page here, the most cited first · [← Jiahui Geng](https://md.research.elamur.ai/free/en/authors/jiahui-geng/)

1. **[Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 182 citations*
2. **[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*
3. **[Benchmarking Vision Language Models for Cultural Understanding](https://md.research.elamur.ai/free/en/papers/nayak-2024-benchmarking-vision-language-models-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shravan Nayak, Kanishk Jain, Rabiul Awal, et al.*2024 · 87 citations*
4. **[MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mediq-question-asking-llms-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.*2024 · 74 citations*
5. **[What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering](https://md.research.elamur.ai/free/en/papers/errica-2025-what-did-i-do-wrong/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Federico Errica, Davide Sanvito, Giuseppe Siracusano, et al.*2025 · 63 citations*
6. **[LUQ: Long-text Uncertainty Quantification for LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2024-luq-long-text-uncertainty-quantification/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Caiqi Zhang, Fangyu Liu, Marco Basaldella, et al.*2024 · 42 citations*
7. **[CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, et al.*2025 · 38 citations*
8. **[People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://md.research.elamur.ai/free/en/papers/russell-2025-people-who-frequently-use-chatgpt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jenna Russell, Marzena Karpinska, Mohit Iyyer*2025 · 33 citations*
9. **[CAMEL-Bench: A Comprehensive Arabic LMM Benchmark](https://md.research.elamur.ai/free/en/papers/ghaboura-2025-camel-bench-comprehensive-arabic-lmm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sara Ghaboura, Ahmed Heakl, Omkar Thawakar, et al.*2025 · 22 citations*
10. **[Can Unconfident LLM Annotations Be Used for Confident Conclusions?](https://md.research.elamur.ai/free/en/papers/gligoric-2025-can-unconfident-llm-annotations-be/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kristina Gligorić, Tijana Zrnic, Cinoo Lee, et al.*2025 · 19 citations*
11. **[Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-token-level-density-based-uncertainty/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.*2025 · 13 citations*
12. **[JEEM: Vision-Language Understanding in Four Arabic Dialects](https://md.research.elamur.ai/free/en/papers/kadaoui-2026-jeem-vision-language-understanding-four/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Karima Kadaoui, Hanin Atwany, Hamdan Al-Ali, et al.*2026 · 11 citations*
13. **[Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-confidence-v-s-critique-decomposition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhe Yang, Yichang Zhang, Yudong Wang, et al.*2025 · 11 citations*
14. **[Diffusion Models Through a Global Lens: Are They Culturally Inclusive?](https://md.research.elamur.ai/free/en/papers/bayramli-2025-diffusion-models-through-global-lens/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zahra Bayramli, Ayhan Suleymanzade, Na Min An, et al.*2025 · 11 citations*
15. **[Grounding Multilingual Multimodal LLMs With Cultural Knowledge](https://md.research.elamur.ai/free/en/papers/nyandwi-2025-grounding-multilingual-multimodal-llms-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jean De Dieu Nyandwi, Yueqi Song, Simran Khanuja, et al.*2025 · 11 citations*
16. **[Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles](https://md.research.elamur.ai/free/en/papers/xia-2025-influences-llm-calibration-study-response/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxi Xia, Pedro Henrique Luz De Araujo, Klim Zaporojets, et al.*2025 · 11 citations*
17. **[Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset](https://md.research.elamur.ai/free/en/papers/alwajih-2025-pearl-multimodal-culturally-aware-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fakhraddin Alwajih, Samar M. Magdy, Abdellah El Mekki, et al.*2025 · 11 citations*
18. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations*
19. **[Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](https://md.research.elamur.ai/free/en/papers/geigle-2025-centurio-drivers-multilingual-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.*2025 · 9 citations*
20. **[DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture](https://md.research.elamur.ai/free/en/papers/maji-2025-drishtikon-multimodal-multilingual-benchmark-testing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Arijit Maji, Raghvendra Kumar, Akash Ghosh, et al.*2025 · 9 citations*
21. **[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*
22. **[Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2025-marco-o1-v2-widening/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huifeng Yin, Yu Zhao, Minghao Wu, et al.*2025 · 8 citations*
23. **[Piecing It All Together: Verifying Multi-Hop Multimodal Claims](https://md.research.elamur.ai/free/en/papers/wang-2025-piecing-it-all-together-verifying/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Haoran Wang, Aman Rangapur, Xiongxiao Xu, et al.*2025 · 8 citations*
24. **[Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?](https://md.research.elamur.ai/free/en/papers/liu-2025-revisiting-epistemic-markers-confidence-estimation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayu Liu, Qing Zong, Weiqi Wang, et al.*2025 · 8 citations*
25. **[Confidence Estimation for LLMs in Multi-turn Interactions](https://md.research.elamur.ai/free/en/papers/zhang-2026-confidence-estimation-llms-multi-turn/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Caiqi Zhang, Ruihan Yang, Xiaochen Zhu, et al.*2026 · 7 citations*
26. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
27. [**OASIS: A Multilingual and Multimodal Dataset for Culturally Grounded Spoken Visual QA arXiv:2510.06371**Firoj Alam, Ali Ezzat Shahroor, Md. Arid Hasan, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/alam-2025-oasis-multilingual-multimodal-dataset-culturally/)
28. **[LLM Alignment for the Arabs: A Homogenous Culture or Diverse Ones](https://md.research.elamur.ai/free/en/papers/keleg-2025-llm-alignment-arabs-homogenous-culture/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Amr Keleg*2025 · 5 citations*
29. **[Marco-Bench-MIF: On Multilingual Instruction-Following Capability of Large Language](https://md.research.elamur.ai/free/en/papers/zeng-2025-marco-bench-mif-multilingual-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Zeng, Chenyang Lyu, Sinuo Liu, et al.*2025 · 5 citations*
30. **[MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training](https://md.research.elamur.ai/free/en/papers/huang-2025-musc-improving-complex-instruction-following/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Huang, Jiaheng Liu, Yancheng He, et al.*2025 · 4 citations*
31. **[Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-audio-jailbreak-open-comprehensive-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zirui Song, Qian Jiang, Mingxuan Cui, et al.*2026 · 3 citations*
32. **[Beyond “I Don't Know”: Evaluating LLM Self-Awareness in Discriminating Data and Model Uncertainty](https://md.research.elamur.ai/free/en/papers/ren-2026-beyond-i-don-t-know/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyi Ren, Ante Wang, Yunghwei Lai, et al.*2026 · 3 citations*
33. **[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*
34. **[AGSC: Adaptive Granularity and Semantic Clustering for Uncertainty Quantification in Long-text Generation](https://md.research.elamur.ai/free/en/papers/luo-2026-agsc-adaptive-granularity-semantic-clustering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanran Luo, Wentao Qiu, Wanru Zhao, et al.*2026 · 2 citations*
35. **[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*
36. **[Comparing Human and Large Language Model Interpretation of Implicit Information](https://md.research.elamur.ai/free/en/papers/santis-2026-comparing-human-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Antonio De Santis, Tommaso Bonetti, Andrea Tocchetti, et al.*2026 · 2 citations*
37. **[Finding Culture-Sensitive Neurons in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2026-finding-culture-sensitive-neurons-vision/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Xiutian Zhao, Rochelle Choenni, Rohit Saxena, et al.*2026 · 2 citations*
38. **[Mind the Gap: Benchmarking LLM Uncertainty and Calibration with Specialty-Aware Clinical QA and Reasoning-Based Behavioural Features](https://md.research.elamur.ai/free/en/papers/testoni-2026-mind-gap-benchmarking-llm-uncertainty/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Alberto Testoni, Iacer Calixto*2026 · 2 citations*
39. **[Once Correct, Still Wrong: Counterfactual Hallucination in Multilingual Vision-Language Models](https://md.research.elamur.ai/free/en/papers/mousi-2026-once-correct-still-wrong-counterfactual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Basel Mousi, Fahim Dalvi, Shammur Absar Chowdhury, et al.*2026 · 2 citations*
40. **[POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering](https://md.research.elamur.ai/free/en/papers/xu-2026-polychartqa-benchmarking-large-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichen Xu, Liangyu Chen, Liang Zhang, et al.*2026 · 2 citations*
41. [**Benchmarking Vision Language Models on German Factual Data arXiv:2504.11108**Rene Peinl, Vincent Tischler*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/peinl-2025-benchmarking-vision-language-models-german/)
42. **[BaseCal: Unsupervised Confidence Calibration via Base Model Signals](https://md.research.elamur.ai/free/en/papers/tan-2026-basecal-unsupervised-confidence-calibration-base/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hexiang Tan, Wanli Yang, Junwei Zhang, et al.*2026 · 1 citation*
43. **[Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration](https://md.research.elamur.ai/free/en/papers/zhong-2026-efficient-self-evaluation-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linhao Zhong, Linyu Wu, Wen Wang, et al.*2026 · 1 citation*
44. **[Frankentext: Stitching random text fragments into long-form narratives](https://md.research.elamur.ai/free/en/papers/pham-2026-frankentext-stitching-random-text-fragments/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chau Minh Pham, Jenna Russell, Dzung Pham, et al.*2026 · 1 citation*
45. **[From Attack Surfaces to Actual Operations: A Survey of Modern LLM Jailbreaks](https://md.research.elamur.ai/free/en/papers/zhou-2026-attack-surfaces-actual-operations-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruikang Zhou, Changsheng Sun, Mark Huasong Meng*2026 · 1 citation*
46. **[From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-passive-metric-active-signal-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxin Zhang, Wendi Cui, Zhuohang Li, et al.*2026 · 1 citation*
47. **[Afri-MCQA: Multimodal Cultural Question Answering for African Languages](https://md.research.elamur.ai/free/en/papers/tonja-2026-afri-mcqa-multimodal-cultural-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atnafu Lambebo Tonja, Srija Anand, Emilio Villa-Cueva, et al.*2026*
48. [**AmharicStoryQA: A Multicultural Story Question Answering Benchmark in Amharic arXiv:2602.02774**Israel Abebe Azime, Abenezer Kebede Angamo, Hana Mekonen Tamiru, et al.*2026*](https://md.research.elamur.ai/free/en/papers/azime-2026-amharicstoryqa-multicultural-story-question-answering/)
49. **[Beyond Noise: Characterizing Creative Potential in Unverifiable LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/yan-2026-beyond-noise-characterizing-creative-potential/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Yan, Chunhong Zhang, Haiyu Zhao, et al.*2026*
50. **[Calibration-Aware Policy Optimization for Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-calibration-aware-policy-optimization-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqi Wang, Xingzhou Lou, Meiqi Wu, et al.*2026*
51. **[Diagnosing LLMs via Information Spectrum Analysis: Tail Behavior and the Effects of Side Information](https://md.research.elamur.ai/free/en/papers/tachioka-2026-diagnosing-llms-information-spectrum-analysis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuuki Tachioka*2026*
52. **[Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026*
53. **[Evaluating Perspectival Biases in Cross-Modal Retrieval](https://md.research.elamur.ai/free/en/papers/saengsukhiran-2026-evaluating-perspectival-biases-cross-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Teerapol Saengsukhiran, Peerawat Chomphooyod, Narabodee Rodjananant, et al.*2026*
54. **[Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for Classification](https://md.research.elamur.ai/free/en/papers/merdjanovska-2026-evaluation-pitfalls-sparsity-limitations-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elena Merdjanovska, Omar Zaidan, Andreas Rücklé*2026*
55. [**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/)
56. [**ImageEval 2026: Culturally Grounded Arabic Multimodal Evaluation arXiv:2608.30475**Samir Abdaljalil, Hunzalah Hassan Bhatti, Ahlam Bashiti, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abdaljalil-2026-imageeval-2026-culturally-grounded-arabic/)
57. **[Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA](https://md.research.elamur.ai/free/en/papers/pei-2026-information-asymmetry-across-language-varieties/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Renhao Pei, Siyao Peng, Verena Blaschke, et al.*2026*
58. **[Mapping the Course for Prompt-based Structured Prediction](https://md.research.elamur.ai/free/en/papers/pauk-2026-mapping-course-prompt-based-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Matt Pauk, Maria Leonor Pacheco*2026*
59. **[Probing and Steering Uncertainty in Biomedical Language Models: Representational Structure and Behavioral Limits](https://md.research.elamur.ai/free/en/papers/pal-2026-probing-steering-uncertainty-biomedical-language/) [BioNLP](https://md.research.elamur.ai/free/en/venues/bionlp/)**Debmalya Pal*2026*
60. **[Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation](https://md.research.elamur.ai/free/en/papers/mule-2026-teaching-language-models-forecast-research/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Srujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan*2026*

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