---
title: "Who cites Dustin Schwenk — page 4 — 1,364 citing papers"
description: "1,364 papers of the Elamur Research library cite the works of Dustin Schwenk, found in their bibliographies · page 4 of 4 · 301–332; the most…"
canonical: "https://research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/4/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/4/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Dustin Schwenk](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/) / [cited by](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/) / page 4

# Who cites Dustin Schwenk

1,670 citations of their works from 1,364 papers of our library (of the 149,439 whose bibliographies we read) · 332 with a page here, the most cited first · page 4 of 4 · 301–332 · [← Dustin Schwenk](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/)

[← prev](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/3/) [1](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/3/) **4**

301. **[Observations and Remedies for Large Language Model Bias in Self-Consuming Performative Loop](https://md.research.elamur.ai/free/en/papers/wang-2026-observations-remedies-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaxuan Wang, Zhongteng Cai, Yujia Bao, et al.*2026*
302. [**Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM Pretraining**Hiroshi Matsuda, Masayuki Asahara*2026*](https://md.research.elamur.ai/free/en/papers/matsuda-2026-probing-dynamics-syntactic-ability-acquisition/)
303. **[Progressive Re-ranking for Multimodal Retrieval-Augmented Generation via Curriculum Learning](https://md.research.elamur.ai/free/en/papers/min-2026-progressive-re-ranking-multimodal-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhu Min, Yanchao Hao, Jian Liu, et al.*2026*
304. **[Reliable Use of Lemmas via Eligibility Reasoning and Section-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xu-2026-reliable-use-lemmas-eligibility-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhikun Xu, Xiaodong Yu, Ben Zhou, et al.*2026*
305. [**Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling arXiv:2604.28075**Ansar Aynetdinov, Patrick Haller, Alan Akbik*2026*](https://md.research.elamur.ai/free/en/papers/aynetdinov-2026-repetition-over-diversity-high-signal/)
306. **[Rethinking Data Mixing from the Perspective of Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-rethinking-data-mixing-perspective-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanjian Xu, Tianze Sun, Changwei Xu, et al.*2026*
307. **[Rethinking the Idiomaticity Decomposability Hypothesis: Evidence from Distributional Learning](https://md.research.elamur.ai/free/en/papers/mi-2026-rethinking-idiomaticity-decomposability-hypothesis-evidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maggie Mi, Golzar Atefi, Atsuki Yamaguchi, et al.*2026*
308. **[Revisiting Non-Verbatim Memorization in Large Language Models: The Role of Entity Surface Forms](https://md.research.elamur.ai/free/en/papers/nishida-2026-revisiting-non-verbatim-memorization-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuto Nishida, Naoki Shikoda, Yosuke Kishinami, et al.*2026*
309. **[Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model Behavior](https://md.research.elamur.ai/free/en/papers/nadkarni-2026-rewriting-history-recipe-interventional-analyses/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Rahul Nadkarni, Yanai Elazar, Hila Gonen, et al.*2026*
310. **[RoleConflictBench: A Benchmark of Role Conflict Scenarios for Evaluating LLMs' Contextual Sensitivity](https://md.research.elamur.ai/free/en/papers/shin-2026-roleconflictbench-benchmark-role-conflict-scenarios/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jisu Shin, Hoyun Song, Juhyun Oh, et al.*2026*
311. **[Scare Quotes as Markers of “Questionable” Word Usages and Misalignment in Conversation: An Annotation Study](https://md.research.elamur.ai/free/en/papers/soler-2026-scare-quotes-as-markers-questionable/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aina Garí Soler, Juan Carlos Zevallos Huaco, Matthieu Labeau, et al.*2026*
312. **[SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes](https://md.research.elamur.ai/free/en/papers/wang-2026-scenealign-aligning-multimodal-reasoning-scene/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chuhan Wang, Xintong Li, Jennifer Yuntong Zhang, et al.*2026*
313. **[SciPedia: Unlocking the Value of Scientific Data for Pre-training](https://md.research.elamur.ai/free/en/papers/qin-2026-scipedia-unlocking-value-scientific-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiwei Qin, Zhen Huang, Tiantian Mi, et al.*2026*
314. **[Sentiment Analysis and Language Models for Kwanyama](https://md.research.elamur.ai/free/en/papers/nakashole-2026-sentiment-analysis-language-models-kwanyama/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ndapa Nakashole*2026*
315. **[SPAGBias: Uncovering and Tracing Structured Spatial Gender Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2026-spagbias-uncovering-tracing-structured-spatial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binxian Su, Haoye Lou, Shucheng Zhu, et al.*2026*
316. **[Suppressing Final Layer Hidden State Jumps in Transformer Pretraining](https://md.research.elamur.ai/free/en/papers/shibata-2026-suppressing-final-layer-hidden-state/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Keigo Shibata, Kazuki Yano, Ryosuke Takahashi, et al.*2026*
317. **[The Challenge of Identifying the Origin of Black-Box Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-challenge-identifying-origin-black-box/) [Workshop on Privacy in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/privatenlp/)**Ziqing Yang, Yixin Wu, Yun Shen, et al.*2026*
318. **[The Conundrum of Trustworthy Research on Attacking Personally Identifiable Information Removal Techniques](https://md.research.elamur.ai/free/en/papers/ochs-2026-conundrum-trustworthy-research-attacking-personally/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Sebastian Ochs, Ivan Habernal*2026*
319. [**The Validity of Coreference-based Evaluations of Natural Language Understanding arXiv:2602.16200**Ian Porada*2026*](https://md.research.elamur.ai/free/en/papers/porada-2026-validity-coreference-based-evaluations-natural/)
320. **[Think Like You Execute: Verifiable Chain of Thought from Program Traces](https://md.research.elamur.ai/free/en/papers/thakur-2026-think-like-you-execute-verifiable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shailja Thakur, Vaibhav Saxena, Rohan Kulkarni, et al.*2026*
321. **[TiKMiX: Efficient Semi-Dynamic Data Mixture via Data Influence for LLM Pre-training](https://md.research.elamur.ai/free/en/papers/wang-2026-tikmix-efficient-semi-dynamic-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifan Wang, Binbinliu, Fengze Liu, et al.*2026*
322. **[Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models](https://md.research.elamur.ai/free/en/papers/shah-2026-too-nice-tell-truth-quantifying/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arya Shah, Deepali Mishra, Chaklam Silpasuwanchai*2026*
323. **[TReX: Tokenizer Regression for Optimal Data Mixture](https://md.research.elamur.ai/free/en/papers/won-2026-trex-tokenizer-regression-optimal-data/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Inho Won, Hangyeol Yoo, Minkyung Cho, et al.*2026*
324. **[VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning](https://md.research.elamur.ai/free/en/papers/xiao-2026-vl-calibration-decoupled-confidence-calibration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenyi Xiao, Xinchi XU, Leilei Gan*2026*
325. **[Weight Tying Biases Token Embeddings Towards the Output Space](https://md.research.elamur.ai/free/en/papers/lopardo-2026-weight-tying-biases-token-embeddings/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Antonio Lopardo, Avyukth Harish, Catherine Arnett, et al.*2026*
326. **[What Does Infect Mean to Cardio? Investigating the Role of Clinical Specialty Data in Medical LLMs](https://md.research.elamur.ai/free/en/papers/yan-2026-what-does-infect-mean-cardio/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Xinlan Yan, Di Wu, Yibin Lei, et al.*2026*
327. **[Who Speaks for Whom? LLM-Generated Survey Data as a Proxy for Public Opinion](https://md.research.elamur.ai/free/en/papers/venkatakrishnan-2026-who-speaks-whom-llm-generated/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Radhakrishnan Venkatakrishnan, Travis Brodbeck, Michael D. Young*2026*
328. **[Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/qian-2026-why-do-large-language-models/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Shenbin Qian, Yves Scherrer*2026*
329. **[xLM: A Python Package for Non-Autoregressive Language Models](https://md.research.elamur.ai/free/en/papers/patel-2026-xlm-python-package-non-autoregressive/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Dhruvesh Patel, Durga Prasad Maram, Sai Sreenivas Chintha, et al.*2026*
330. [**Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMs**William Sheffield, Kanishka Misra, Valentina Pyatkin, et al.*2025*](https://md.research.elamur.ai/free/en/papers/sheffield-2025-is-it-textit-just-semantics/)
331. [**Social Perceptions of English Spelling Variation on Twitter: A Comparative Analysis of Human and LLM Responses arXiv:2511.23041**Dong Nguyen, Laura Rosseel*2025*](https://md.research.elamur.ai/free/en/papers/nguyen-2025-social-perceptions-english-spelling-variation/)
332. [**360Zhinao Technical Report arXiv:2405.13386***2024*](https://md.research.elamur.ai/free/en/papers/360zhinao-team-2024-360zhinao-technical-report/)

[← prev](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/3/) [1](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/cited-by/page/3/) **4**

1,032 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/dustin-schwenk/) — Dustin Schwenk