---
title: "Who cites Danilo Jimenez Rezende — 825 papers of our library"
description: "825 papers of the Elamur Research library cite the works of Danilo Jimenez Rezende, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/danilo-jimenez-rezende/cited-by/"
---
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# Who cites Danilo Jimenez Rezende

994 citations of their works from 825 papers of our library (of the 149,439 whose bibliographies we read) · 73 with a page here, the most cited first · [← Danilo Jimenez Rezende](https://md.research.elamur.ai/free/en/authors/danilo-jimenez-rezende/)

1. [**Auto-Encoding Variational Bayes arXiv:1312.6114**Diederik P Kingma, Max Welling*2013 · 15,450 citations*](https://md.research.elamur.ai/free/en/papers/kingma-2013-auto-encoding-variational-bayes/)
2. [**Language Models are Few-Shot Learners arXiv:2005.14165**Tom B. Brown, Benjamin Mann, Nick Ryder, et al.*2020 · 14,178 citations*](https://md.research.elamur.ai/free/en/papers/brown-2020-language-models-few-shot-learners/)
3. **[Effective Approaches to Attention-based Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thang Luong, Hieu Pham, Christopher D. Manning*2015 · 9,718 citations*
4. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
5. [**Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks arXiv:1511.06434**Alec Radford, Luke Metz, Soumith Chintala*2015 · 6,654 citations*](https://md.research.elamur.ai/free/en/papers/radford-2015-unsupervised-representation-learning-deep-convolutional/)
6. [**Generative Adversarial Nets**Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, et al.*2014 · 5,790 citations*](https://md.research.elamur.ai/free/en/papers/goodfellow-2014-generative-adversarial-nets/)
7. [**Teaching Machines to Read and Comprehend arXiv:1506.03340**Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, et al.*2015 · 3,858 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2015-teaching-machines-read-comprehend/)
8. [**Neural Message Passing for Quantum Chemistry arXiv:1704.01212**Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, et al.*2017 · 3,793 citations*](https://md.research.elamur.ai/free/en/papers/gilmer-2017-neural-message-passing-quantum-chemistry/)
9. [**Categorical Reparameterization with Gumbel-Softmax arXiv:1611.01144**Eric Jang, Shixiang Gu, Ben Poole*2016 · 3,656 citations*](https://md.research.elamur.ai/free/en/papers/jang-2016-categorical-reparameterization-gumbel-softmax/)
10. **[Generating Sentences from a Continuous Space](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,435 citations*
11. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
12. [**High-Resolution Image Synthesis with Latent Diffusion Models arXiv:2112.10752**Robin Rombach, Andreas Blattmann, Dominik Lorenz, et al.*2021 · 1,996 citations*](https://md.research.elamur.ai/free/en/papers/rombach-2021-high-resolution-image-synthesis-latent/)
13. [**Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848**Qizhe Xie, Zihang Dai, Eduard Hovy, et al.*2019 · 1,871 citations*](https://md.research.elamur.ai/free/en/papers/xie-2019-unsupervised-data-augmentation-consistency-training/)
14. [**Layer Normalization arXiv:1607.06450**Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton*2016 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)
15. [**Deep Unsupervised Learning using Nonequilibrium Thermodynamics arXiv:1503.03585**Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, et al.*2015 · 1,761 citations*](https://md.research.elamur.ai/free/en/papers/sohl-dickstein-2015-deep-unsupervised-learning-using-nonequilibrium/)
16. [**The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables arXiv:1611.00712**Chris J. Maddison, Andriy Mnih, Yee Whye Teh*2016 · 1,629 citations*](https://md.research.elamur.ai/free/en/papers/maddison-2016-concrete-distribution-continuous-relaxation-discrete/)
17. [**Improved Techniques for Training GANs arXiv:1606.03498**Tim Salimans, Ian Goodfellow, Wojciech Zaremba, et al.*2016 · 1,558 citations*](https://md.research.elamur.ai/free/en/papers/salimans-2016-improved-techniques-training-gans/)
18. **[Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elena Voita, David Talbot, Fedor Moiseev, et al.*2019 · 1,535 citations*
19. [**Zero-Shot Text-to-Image Generation arXiv:2102.12092**Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)
20. [**Variational Inference with Normalizing Flows**Danilo Jimenez Rezende, Shakir Mohamed*2015 · 1,441 citations*](https://md.research.elamur.ai/free/en/papers/rezende-2015-variational-inference-normalizing-flows/)
21. [**Generative Modeling by Estimating Gradients of the Data Distribution arXiv:1907.05600**Yang Song, Stefano Ermon*2019 · 1,274 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/)
22. **[WaveGlow: A Flow-based Generative Network for Speech Synthesis](https://md.research.elamur.ai/free/en/papers/prenger-2018-waveglow-flow-based-generative-network/) [IEEE International Conference on Acoustics Speech and Signal Processing](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-acoustics-speech-and-signal-processing/)**Ryan Prenger, Rafael Valle, Bryan Catanzaro*2018 · 1,055 citations*
23. **[ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs](https://md.research.elamur.ai/free/en/papers/yin-2016-abcnn-attention-based-convolutional-neural/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Wenpeng Yin, Hinrich Schütze, Bing Xiang, et al.*2016 · 1,055 citations*
24. [**A Theoretically Grounded Application of Dropout in Recurrent Neural Networks arXiv:1512.05287**Yarin Gal, Zoubin Ghahramani*2015 · 1,032 citations*](https://md.research.elamur.ai/free/en/papers/gal-2015-theoretically-grounded-application-dropout-recurrent/)
25. **[Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders](https://md.research.elamur.ai/free/en/papers/zhao-2017-learning-discourse-level-diversity-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Zhao, Ran Zhao, Maxine Eskenazi*2017 · 993 citations*
26. **[Visual7W: Grounded Question Answering in Images](https://md.research.elamur.ai/free/en/papers/zhu-2015-visual7w-grounded-question-answering-images/) [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/)**Yuke Zhu, Oliver Groth, Michael Bernstein, et al.*2015 · 952 citations*
27. [**DRAW: A Recurrent Neural Network For Image Generation arXiv:1502.04623**Karol Gregor, Ivo Danihelka, Alex Graves, et al.*2015 · 947 citations*](https://md.research.elamur.ai/free/en/papers/gregor-2015-draw-recurrent-neural-network-image/)
28. **[Efficient Content-Based Sparse Attention with Routing Transformers](https://md.research.elamur.ai/free/en/papers/roy-2020-efficient-content-based-sparse-attention/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aurko Roy, Mohammad Saffar, Ashish Vaswani, et al.*2020 · 677 citations*
29. [**How Powerful are Graph Neural Networks? arXiv:1810.00826**Keyulu Xu, Weihua Hu, Jure Leskovec, et al.*2018 · 655 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-powerful-graph-neural-networks/)
30. [**A simple neural network module for relational reasoning arXiv:1706.01427**Adam Santoro, David Raposo, David G. T. Barrett, et al.*2017 · 632 citations*](https://md.research.elamur.ai/free/en/papers/santoro-2017-simple-neural-network-module-relational/)
31. **[Harnessing Deep Neural Networks with Logic Rules](https://md.research.elamur.ai/free/en/papers/hu-2016-harnessing-deep-neural-networks-logic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, et al.*2016 · 627 citations*
32. [**Denoising Diffusion Implicit Models arXiv:2010.02502**Jiaming Song, Chenlin Meng, Stefano Ermon*2020 · 576 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-denoising-diffusion-implicit-models/)
33. **[A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues](https://md.research.elamur.ai/free/en/papers/serban-2016-hierarchical-latent-variable-encoder-decoder/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, et al.*2016 · 547 citations*
34. [**Toward Controlled Generation of Text arXiv:1703.00955**Zhiting Hu, Zichao Yang, Xiaodan Liang, et al.*2017 · 537 citations*](https://md.research.elamur.ai/free/en/papers/hu-2017-toward-controlled-generation-text/)
35. [**CogView: Mastering Text-to-Image Generation via Transformers arXiv:2105.13290**Ming Ding, Zhuoyi Yang, Wenyi Hong, et al.*2021 · 469 citations*](https://md.research.elamur.ai/free/en/papers/ding-2021-cogview-mastering-text-image/)
36. [**Diffusion-LM Improves Controllable Text Generation arXiv:2205.14217**Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, et al.*2022 · 440 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-diffusion-lm-improves-controllable-text/)
37. **[WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents](https://md.research.elamur.ai/free/en/papers/yao-2022-webshop-towards-scalable-real-world/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shunyu Yao, Howard Chen, John Yang, et al.*2022 · 420 citations*
38. [**Learning Latent Dynamics for Planning from Pixels arXiv:1811.04551**Danijar Hafner, Timothy Lillicrap, Ian Fischer, et al.*2018 · 394 citations*](https://md.research.elamur.ai/free/en/papers/hafner-2018-learning-latent-dynamics-planning-pixels/)
39. [**The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence arXiv:2002.06177**Gary Marcus*2020 · 332 citations*](https://md.research.elamur.ai/free/en/papers/marcus-2020-next-decade-ai-four/)
40. [**Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow arXiv:2209.03003**Xingchao Liu, Chengyue Gong, Qiang Liu*2022 · 315 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-flow-straight-fast-learning-generate/)
41. [**Structured Denoising Diffusion Models in Discrete State-Spaces arXiv:2107.03006**Jacob Austin, Daniel D. Johnson, Jonathan Ho, et al.*2021 · 284 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-structured-denoising-diffusion-models-discrete/)
42. **[Variational Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2016-variational-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Biao Zhang, Deyi Xiong, Jinsong Su, et al.*2016 · 283 citations*
43. **[MIME: MIMicking Emotions for Empathetic Response Generation](https://md.research.elamur.ai/free/en/papers/majumder-2020-mime-mimicking-emotions-empathetic-response/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Navonil Majumder, Pengfei Hong, Shanshan Peng, et al.*2020 · 278 citations*
44. **[Logic Tensor Networks](https://md.research.elamur.ai/free/en/papers/badreddine-2020-logic-tensor-networks/) [Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/artificial-intelligence/)**Samy Badreddine, Artur d'Avila Garcez, Luciano Serafini, et al.*2020 · 276 citations*
45. **[Survey of Low-Resource Machine Translation](https://md.research.elamur.ai/free/en/papers/haddow-2022-survey-low-resource-machine-translation/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.*2022 · 251 citations*
46. [**A Deep Generative Framework for Paraphrase Generation arXiv:1709.05074**Ankush Gupta, Arvind Agarwal, Prawaan Singh, et al.*2017 · 233 citations*](https://md.research.elamur.ai/free/en/papers/gupta-2017-deep-generative-framework-paraphrase-generation/)
47. **[FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow](https://md.research.elamur.ai/free/en/papers/ma-2019-flowseq-non-autoregressive-conditional-sequence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuezhe Ma, Chunting Zhou, Xian Li, et al.*2019 · 218 citations*
48. **[Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space](https://md.research.elamur.ai/free/en/papers/li-2020-optimus-organizing-sentences-pre-trained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chunyuan Li, Xiang Gao, Yuan Li, et al.*2020 · 208 citations*
49. **[Training Question Answering Models From Synthetic Data](https://md.research.elamur.ai/free/en/papers/puri-2020-training-question-answering-models-synthetic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Raul Puri, Ryan Spring, Mohammad Shoeybi, et al.*2020 · 208 citations*
50. **[Compound Probabilistic Context-Free Grammars for Grammar Induction](https://md.research.elamur.ai/free/en/papers/kim-2019-compound-probabilistic-context-free-grammars/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoon Kim, Chris Dyer, Alexander Rush*2019 · 201 citations*
51. **[Representation of Linguistic Form and Function in Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/kadar-2017-representation-linguistic-form-function-recurrent/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ákos Kádár, Grzegorz Chrupała, Afra Alishahi*2017 · 192 citations*
52. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
53. **[Neural Net Models of Open-domain Discourse Coherence](https://md.research.elamur.ai/free/en/papers/li-2017-neural-net-models-open-domain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiwei Li, Dan Jurafsky*2017 · 147 citations*
54. **[Interpretable Neural Predictions with Differentiable Binary Variables](https://md.research.elamur.ai/free/en/papers/bastings-2019-interpretable-neural-predictions-differentiable-binary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jasmijn Bastings, Wilker Aziz, Ivan Titov*2019 · 135 citations*
55. [**Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration arXiv:1802.08802**Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, et al.*2018 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-reinforcement-learning-web-interfaces-using/)
56. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
57. [**PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis arXiv:2310.00426**Junsong Chen, Jincheng Yu, Chongjian Ge, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-pixart-alpha-fast-training-diffusion/)
58. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
59. **[Topic Tensor Network for Implicit Discourse Relation Recognition in Chinese](https://md.research.elamur.ai/free/en/papers/xu-2019-topic-tensor-network-implicit-discourse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sheng Xu, Peifeng Li, Fang Kong, et al.*2019 · 31 citations*
60. **[Variational Neural Discourse Relation Recognizer](https://md.research.elamur.ai/free/en/papers/zhang-2016-variational-neural-discourse-relation-recognizer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Biao Zhang, Deyi Xiong, Jinsong Su, et al.*2016 · 30 citations*
61. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
62. **[Improving Event Coreference Resolution Using Document-level and Topic-level Information](https://md.research.elamur.ai/free/en/papers/xu-2022-improving-event-coreference-resolution-document/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sheng Xu, Peifeng Li, Qiaoming Zhu*2022 · 15 citations*
63. **[Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/sui-2026-meta-reasoner-dynamic-guidance-optimized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Sui, Yufei He, Tri Cao, et al.*2026 · 13 citations*
64. **[Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://md.research.elamur.ai/free/en/papers/akter-2026-nemotron-crossthink-scaling-self-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.*2026 · 9 citations*
65. **[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*
66. **[GAM: Hierarchical Graph-based Agentic Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/wu-2026-gam-hierarchical-graph-based-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaofen Wu, Hanrong Zhang, Fulin Lin, et al.*2026 · 5 citations*
67. **[Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models](https://md.research.elamur.ai/free/en/papers/nguyen-2026-beyond-coherence-improving-temporal-consistency/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thanh Vinh Nguyen, Ngo Van Dong, Minh Chu Xuan, et al.*2026 · 1 citation*
68. **[CityCube: Benchmarking Cross-view Spatial Reasoning on Vision-Language Models in Urban Environments](https://md.research.elamur.ai/free/en/papers/xu-2026-citycube-benchmarking-cross-view-spatial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haotian Xu, Yue Hu, Zhengqiu Zhu, et al.*2026 · 1 citation*
69. **[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*
70. **[FLAIR: Steering LLM Mathematical Problem Solving based on A Fuzzy-Logic-AssIsted Reasoner](https://md.research.elamur.ai/free/en/papers/wu-2026-flair-steering-llm-mathematical-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wu, Hongru Sun, Wanqing Li, et al.*2026*
71. **[Flow-Based Page Unique Semantic Mapping Architecture for Document Visual Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2026-flow-based-page-unique-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haosen Wang, Jing Xiao, Chaochao Du, et al.*2026*
72. [**Recent Advances in Text-attributed Graph Learning via Large Models (大模型驱动的文本属性图学习研究进展) Acta Automatica Sinica (自动化学报)**Yanping Zheng (郑艳萍), Jiarui Ji (季嘉蕊), Yuwei Hu (胡雨韦), et al.*2026*](https://md.research.elamur.ai/free/en/papers/zheng-2026-recent-advances-text/)
73. **[Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-skill-aware-data-selection-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lechen Zhang, Yunxiang Zhang, Wei Hu, et al.*2026*

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