---
title: "Who cites Adam: A Method for Stochastic Optimization — page 8"
description: "10,909 papers of the Elamur Research library cite «Adam: A Method for Stochastic Optimization», found in their bibliographies · page 8 of 12…"
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# Who cites «Adam: A Method for Stochastic Optimization»

10,909 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1123 with a page here, the most cited first · page 8 of 12 · 701–800 · [← back to «Adam: A Method for Stochastic Optimization»](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/)

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701. **[D4: Improving LLM Pretraining via Document De-Duplication and Diversification](https://md.research.elamur.ai/free/en/papers/tirumala-2023-d4-improving-llm-pretraining-document/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.*2023 · 81 citations*
702. **[Interpretability at Scale: Identifying Causal Mechanisms in Alpaca](https://md.research.elamur.ai/free/en/papers/wu-2023-interpretability-scale-identifying-causal-mechanisms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Atticus Geiger, Thomas Icard, et al.*2023 · 81 citations*
703. [**Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models arXiv:2307.14539**Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-jailbreak-pieces-compositional-adversarial-attacks/)
704. **[Coreference-Aware Dialogue Summarization](https://md.research.elamur.ai/free/en/papers/liu-2021-coreference-aware-dialogue-summarization/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Zhengyuan Liu, Ke Shi, Nancy Chen*2021 · 81 citations*
705. **[Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks](https://md.research.elamur.ai/free/en/papers/toshniwal-2020-learning-ignore-long-document-coreference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shubham Toshniwal, Sam Wiseman, Allyson Ettinger, et al.*2020 · 80 citations*
706. **[AraGPT2: Pre-Trained Transformer for Arabic Language Generation](https://md.research.elamur.ai/free/en/papers/antoun-2021-aragpt2-pre-trained-transformer-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Wissam Antoun, Fady Baly, Hazem Hajj*2021 · 79 citations*
707. [**Evaluating prose style transfer with the Bible**Keith Carlson, Allen Riddell, Daniel Rockmore*2017 · 78 citations*](https://md.research.elamur.ai/free/en/papers/carlson-2017-evaluating-prose-style-transfer-bible/)
708. [**Time-LLM: Time Series Forecasting by Reprogramming Large Language Models arXiv:2310.01728**Ming Jin, Shiyu Wang, Lintao Ma, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/jin-2023-time-llm-time-series-forecasting/)
709. **[Multi-dialect Arabic BERT for Country-level Dialect Identification](https://md.research.elamur.ai/free/en/papers/talafha-2020-multi-dialect-arabic-bert-country/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Bashar Talafha, Mohammad Ali, Muhy Eddin Za'ter, et al.*2020 · 77 citations*
710. **[Improving Compositional Generalization with Latent Structure and Data Augmentation](https://md.research.elamur.ai/free/en/papers/qiu-2022-improving-compositional-generalization-latent-structure/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Linlu Qiu, Peter Shaw, Panupong Pasupat, et al.*2022 · 76 citations*
711. **[SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser](https://md.research.elamur.ai/free/en/papers/zhang-2022-syngec-syntax-enhanced-grammatical-error/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yue Zhang, Bo Zhang, Zhenghua Li, et al.*2022 · 76 citations*
712. **[JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation](https://md.research.elamur.ai/free/en/papers/agashe-2019-juice-large-scale-distantly-supervised/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer*2019 · 75 citations*
713. **[Training Language Models to Reason Efficiently](https://md.research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Daman Arora, Andrea Zanette*2025 · 74 citations*
714. [**QuRating: Selecting High-Quality Data for Training Language Models arXiv:2402.09739**Alexander Wettig, Aatmik Gupta, Saumya Malik, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/wettig-2024-qurating-selecting-high-quality-data/)
715. [**ReLoRA: High-Rank Training Through Low-Rank Updates arXiv:2307.05695**Vladislav Lialin, Namrata Shivagunde, Sherin Muckatira, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-relora-high-rank-training-through/)
716. **[NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs](https://md.research.elamur.ai/free/en/papers/baziotis-2018-ntua-slp-semeval-2018-task-s18-1100/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Christos Baziotis, Athanasiou Nikolaos, Pinelopi Papalampidi, et al.*2018 · 74 citations*
717. [**What Language Model to Train if You Have One Million GPU Hours? arXiv:2210.15424**Teven Le Scao, Thomas Wang, Daniel Hesslow, et al.*2022 · 73 citations*](https://md.research.elamur.ai/free/en/papers/scao-2022-language-model-train-if-have/)
718. [**A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering arXiv:2005.05257**Nils Holzenberger, Andrew Blair-Stanek, Benjamin Van Durme*2020 · 73 citations*](https://md.research.elamur.ai/free/en/papers/holzenberger-2020-dataset-statutory-reasoning-tax-law/)
719. **[Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition](https://md.research.elamur.ai/free/en/papers/yang-2018-joint-modeling-accents-acoustics-multi/) [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/)**Xuesong Yang, Kartik Audhkhasi, Andrew Rosenberg, et al.*2018 · 73 citations*
720. [**Systematic Generalization: What Is Required and Can It Be Learned? arXiv:1811.12889**Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, et al.*2018 · 73 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2018-systematic-generalization-required-learned/)
721. [**They, Them, Theirs: Rewriting with Gender-Neutral English arXiv:2102.06788**Tony Sun, Kellie Webster, Apu Shah, et al.*2021 · 72 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-they-them-theirs-rewriting-gender/)
722. **[Better Document-Level Machine Translation with Bayes' Rule](https://md.research.elamur.ai/free/en/papers/yu-2020-better-document-level-machine-translation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Lei Yu, Laurent Sartran, Wojciech Stokowiec, et al.*2020 · 72 citations*
723. **[Finding the Optimal Vocabulary Size for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gowda-2020-finding-optimal-vocabulary-size-neural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thamme Gowda, Jonathan May*2020 · 72 citations*
724. **[Evaluating BERT for natural language inference: A case study on the CommitmentBank](https://md.research.elamur.ai/free/en/papers/jiang-2019-evaluating-bert-natural-language-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nanjiang Jiang, Marie-Catherine de Marneffe*2019 · 72 citations*
725. **[Towards Robustifying NLI Models Against Lexical Dataset Biases](https://md.research.elamur.ai/free/en/papers/zhou-2020-robustifying-nli-models-against-lexical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiang Zhou, Mohit Bansal*2020 · 70 citations*
726. **[Representation Learning for Grounded Spatial Reasoning](https://md.research.elamur.ai/free/en/papers/janner-2018-representation-learning-grounded-spatial-reasoning/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Michael Janner, Karthik Narasimhan, Regina Barzilay*2018 · 70 citations*
727. [**CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation arXiv:2311.18702**Pei Ke, Bosi Wen, Zhuoer Feng, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/ke-2023-critiquellm-informative-critique-generation/)
728. **[How Furiously Can Colorless Green Ideas Sleep? Sentence Acceptability in Context](https://md.research.elamur.ai/free/en/papers/lau-2020-how-furiously-can-colorless-green/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jey Han Lau, Carlos Armendariz, Shalom Lappin, et al.*2020 · 69 citations*
729. **[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*
730. **[Augmenting Transformers with KNN-Based Composite Memory for Dialog](https://md.research.elamur.ai/free/en/papers/fan-2021-augmenting-transformers-knn-based-composite/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Angela Fan, Claire Gardent, Chloé Braud, et al.*2021 · 68 citations*
731. **[A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context](https://md.research.elamur.ai/free/en/papers/udagawa-2019-natural-language-corpus-common-grounding/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Takuma Udagawa, Akiko Aizawa*2019 · 68 citations*
732. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
733. **[Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints](https://md.research.elamur.ai/free/en/papers/wang-2020-faithful-neural-table-text-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenyi Wang, Xiaoyang Wang, Bang An, et al.*2020 · 67 citations*
734. **[Dynamic Routing Transformer Network for Multimodal Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/tian-2023-dynamic-routing-transformer-network-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuan Tian, Nan Xu, Ruike Zhang, et al.*2023 · 66 citations*
735. **[Multi-Domain Dialogue Acts and Response Co-Generation](https://md.research.elamur.ai/free/en/papers/wang-2020-multi-domain-dialogue-acts-response/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Wang, Junfeng Tian, Rui Wang, et al.*2020 · 66 citations*
736. [**Inquisitive Question Generation for High Level Text Comprehension**Wei-Jen Ko, Te-yuan Chen, Yiyan Huang, et al.*2020 · 65 citations*](https://md.research.elamur.ai/free/en/papers/ko-2020-inquisitive-question-generation-high-level/)
737. **[RNNs can generate bounded hierarchical languages with optimal memory](https://md.research.elamur.ai/free/en/papers/hewitt-2020-rnns-can-generate-bounded-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Hewitt, Michael Hahn, Surya Ganguli, et al.*2020 · 65 citations*
738. **[SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution](https://md.research.elamur.ai/free/en/papers/wei-2025-swe-rl-advancing-llm-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Olivier Duchenne, Jade Copet, et al.*2025 · 64 citations*
739. [**Do Neural Language Representations Learn Physical Commonsense? arXiv:1908.02899**Maxwell Forbes, Ari Holtzman, Yejin Choi*2019 · 64 citations*](https://md.research.elamur.ai/free/en/papers/forbes-2019-do-neural-language-representations-learn/)
740. **[Cross-document Coreference Resolution over Predicted Mentions](https://md.research.elamur.ai/free/en/papers/cattan-2021-cross-document-coreference-resolution-over/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arie Cattan, Alon Eirew, Gabriel Stanovsky, et al.*2021 · 63 citations*
741. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/)
742. **[FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models](https://md.research.elamur.ai/free/en/papers/dobler-2023-focus-effective-embedding-initialization-monolingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Konstantin Dobler, Gerard de Melo*2023 · 62 citations*
743. [**Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data Proceedings of the First International Workshop on Natural Language Processing Beyond Text**Xinyu Wang, Xiaowen Sun, Tan Yang, et al.*2020 · 62 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-building-bridge-method-image-text/)
744. **[Posing Fair Generalization Tasks for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/geiger-2019-posing-fair-generalization-tasks-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Atticus Geiger, Ignacio Cases, Lauri Karttunen, et al.*2019 · 61 citations*
745. **[Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks](https://md.research.elamur.ai/free/en/papers/asai-2022-evidentiality-guided-generation-knowledge-intensive/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Matt Gardner, Hannaneh Hajishirzi*2022 · 60 citations*
746. [**AdaMerging: Adaptive Model Merging for Multi-Task Learning arXiv:2310.02575**Enneng Yang, Zhenyi Wang, Li Shen, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-adamerging-adaptive-model-merging-multi/)
747. [**Investigating the Catastrophic Forgetting in Multimodal Large Language Models arXiv:2309.10313**Yuexiang Zhai, Shengbang Tong, Xiao Li, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/zhai-2023-investigating-catastrophic-forgetting-multimodal-large/)
748. **[Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ma-2022-linguistic-rules-based-corpus-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shirong Ma, Yinghui Li, Rongyi Sun, et al.*2022 · 59 citations*
749. **[Target-Aware Data Augmentation for Stance Detection](https://md.research.elamur.ai/free/en/papers/li-2021-target-aware-data-augmentation-stance/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yingjie Li, Cornelia Caragea*2021 · 56 citations*
750. **[Hello Again! LLM-powered Personalized Agent for Long-term Dialogue](https://md.research.elamur.ai/free/en/papers/li-2025-hello-again-llm-powered-personalized/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hao Li, Chenghao Yang, An Zhang, et al.*2025 · 55 citations*
751. [**Harnessing the linguistic signal to predict scalar inferences**Sebastian Schuster, Yuxing Chen, Judith Degen*2020 · 54 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2020-harnessing-linguistic-signal-predict-scalar/)
752. **[A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsing](https://md.research.elamur.ai/free/en/papers/yan-2020-graph-based-model-joint-chinese/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Hang Yan, Xipeng Qiu, Xuanjing Huang*2020 · 53 citations*
753. **[The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue](https://md.research.elamur.ai/free/en/papers/haber-2019-photobook-dataset-building-common-ground/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Janosch Haber, Tim Baumgärtner, Ece Takmaz, et al.*2019 · 53 citations*
754. [**Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics arXiv:2410.21272**Yaniv Nikankin, Anja Reusch, Aaron Mueller, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/nikankin-2024-arithmetic-algorithms-language-models-solve/)
755. **[No Army, No Navy: BERT Semi-Supervised Learning of Arabic Dialects](https://md.research.elamur.ai/free/en/papers/zhang-2019-no-army-no-navy-bert/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Chiyu Zhang, Muhammad Abdul-Mageed*2019 · 51 citations*
756. [**WebLINX: Real-World Website Navigation with Multi-Turn Dialogue arXiv:2402.05930**Xing Han Lu, Zden\vek Kasner, Siva Reddy*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-weblinx-real-world-website-navigation/)
757. **[Word Embeddings Are Steers for Language Models](https://md.research.elamur.ai/free/en/papers/han-2024-word-embeddings-are-steers-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chi Han, Jialiang Xu, Manling Li, et al.*2024 · 49 citations*
758. **[ID10M: Idiom Identification in 10 Languages](https://md.research.elamur.ai/free/en/papers/tedeschi-2022-id10m-idiom-identification-10-languages/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Simone Tedeschi, Federico Martelli, Roberto Navigli*2022 · 49 citations*
759. [**PanGu-Coder: Program Synthesis with Function-Level Language Modeling arXiv:2207.11280**Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.*2022 · 49 citations*](https://md.research.elamur.ai/free/en/papers/christopoulou-2022-pangu-coder-program-synthesis/)
760. [**Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer**Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, et al.*2021 · 49 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/)
761. **[On the limit of English conversational speech recognition](https://md.research.elamur.ai/free/en/papers/tuske-2021-limit-english-conversational-speech-recognition/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Zoltan Tuske, George Saon, Brian Kingsbury*2021 · 49 citations*
762. [**A Neural Entity Coreference Resolution Review Expert Systems with Applications, Volume 168, 15 April 2021, 114,466**Nikolaos Stylianou, Ioannis Vlahavas*2019 · 48 citations*](https://md.research.elamur.ai/free/en/papers/stylianou-2019-neural-entity-coreference-resolution-review/)
763. **[Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-rethinking-kullback-leibler-divergence-knowledge/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Taiqiang Wu, Chaofan Tao, Jiahao Wang, et al.*2025 · 47 citations*
764. [**MIDAS: A Dialog Act Annotation Scheme for Open Domain Human-Machine Spoken Conversations**Dian Yu, Zhou Yu*2021 · 47 citations*](https://md.research.elamur.ai/free/en/papers/yu-2021-midas-dialog-act-annotation-scheme/)
765. **[A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/bothe-2018-context-based-approach-dialogue-act/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Chandrakant Bothe, Cornelius Weber, Sven Magg, et al.*2018 · 46 citations*
766. **[On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition](https://md.research.elamur.ai/free/en/papers/cerisara-2020-effects-using-word2vec-representations-neural/) [Computer Speech & Language](https://md.research.elamur.ai/free/en/venues/computer-speech-language/)**Christophe Cerisara, Pavel Kral, Ladislav Lenc*2017 · 46 citations*
767. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
768. [**Scaling Laws for Generative Mixed-Modal Language Models arXiv:2301.03728**Armen Aghajanyan, Lili Yu, Alexis Conneau, et al.*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/)
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779. [**The MiniPile Challenge for Data-Efficient Language Models arXiv:2304.08442**Jean Kaddour*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-minipile-challenge-data-efficient-language/)
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783. [**PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing arXiv:2303.10845**Xiaozhe Ren, Pingyi Zhou, Xinfan Meng, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ren-2023-pangu-sigma-trillion-parameter/)
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786. [**Aligning Language Models with Preferences through f-divergence Minimization arXiv:2302.08215**Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/go-2023-aligning-language-models-preferences-through/)
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