---
title: "Who cites Saumya Malik — page 3 — 819 papers of our library"
description: "819 papers of the Elamur Research library cite the works of Saumya Malik, found in their bibliographies · page 3 of 3 · 201–241; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/saumya-malik/cited-by/page/3/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/saumya-malik/cited-by/page/3/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Saumya Malik](https://md.research.elamur.ai/free/en/authors/saumya-malik/) / [cited by](https://md.research.elamur.ai/free/en/authors/saumya-malik/cited-by/) / page 3

# Who cites Saumya Malik

920 citations of their works from 819 papers of our library (of the 149,439 whose bibliographies we read) · 241 with a page here, the most cited first · page 3 of 3 · 201–241 · [← Saumya Malik](https://md.research.elamur.ai/free/en/authors/saumya-malik/)

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

201. **[LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points](https://md.research.elamur.ai/free/en/papers/zhang-2026-linkqa-synthesizing-diverse-qa-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuemiao Zhang, Can Ren, Chengying Tu, et al.*2026*
202. **[Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance](https://md.research.elamur.ai/free/en/papers/seegmiller-2026-measuring-distribution-shift-user-prompts/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Seegmiller, Sarah Masud Preum*2026*
203. **[MUC-4 Revisited: Document-level Event Analysis beyond Span-based Arguments](https://md.research.elamur.ai/free/en/papers/olsen-2026-muc-4-revisited-document-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Helene Bøsei Olsen, Erik Velldal, Lilja Øvrelid*2026*
204. **[MUTANT: A Recipe for Multilingual Tokenizer Design](https://md.research.elamur.ai/free/en/papers/rana-2026-mutant-recipe-multilingual-tokenizer-design/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.*2026*
205. **[NegNLI-BR: A Brazilian Portuguese Benchmark for Negation in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/westhelle-2026-negnli-br-brazilian-portuguese-benchmark/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Matheus Westhelle, Viviane Moreira*2026*
206. **[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*
207. **[On the Editability of Delta Parameters in Post-Trained Models](https://md.research.elamur.ai/free/en/papers/tang-2026-editability-delta-parameters-post-trained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiaoyu Tang, Le Yu, Bowen Yu, et al.*2026*
208. **[Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL](https://md.research.elamur.ai/free/en/papers/wu-2026-parallel-sft-improving-zero-shot/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhaofeng Wu, Shiqi Wang, Boya Peng, et al.*2026*
209. **[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*
210. **[PretrainRL: Alleviating Factuality Hallucination of Large Language Models at the Beginning](https://md.research.elamur.ai/free/en/papers/liu-2026-pretrainrl-alleviating-factuality-hallucination-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Langming Liu, Kangtao Lv, Haibin Chen, et al.*2026*
211. [**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/)
212. [**Qwen3.8-Omni: Towards Native Omni-Modal Agents arXiv:2609.25611**Qwen Team*2026*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-8-omni-native/)
213. **[Reinforcement Learning for Latent-Space Thinking in LLMs](https://md.research.elamur.ai/free/en/papers/ozeren-2026-reinforcement-learning-latent-space-thinking/) [Edition of the Swiss Text Analytics Conference](https://md.research.elamur.ai/free/en/venues/swisstext/)**Enes Özeren, Matthias Assenmacher*2026*
214. **[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*
215. **[RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-Context](https://md.research.elamur.ai/free/en/papers/petty-2026-relic-evaluating-complex-reasoning-recognition/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jackson Petty, Michael Y. Hu, Wentao Wang, et al.*2026*
216. **[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*
217. **[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*
218. **[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*
219. **[Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty](https://md.research.elamur.ai/free/en/papers/xiao-2026-revisiting-self-play-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.*2026*
220. **[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*
221. **[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*
222. **[Targeted Exploration via Unified Entropy Control for Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-targeted-exploration-unified-entropy-control/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Wang, Lai Wei, Yanzhi Zhang, et al.*2026*
223. **[The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-art-mis-alignment-how-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Zhang, Hongwei Li, Yun Shen, et al.*2026*
224. **[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*
225. **[TinyJudge: Unverifiable Constraint Alignment via Lightweight Specialist Ensembles](https://md.research.elamur.ai/free/en/papers/zeng-2026-tinyjudge-unverifiable-constraint-alignment-lightweight/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yirong Zeng, Yufei Liu, Xiao Ding, et al.*2026*
226. **[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*
227. **[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*
228. **[Understanding and Mitigating Spurious Signal Amplification in Test-Time Reinforcement Learning for Math Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2026-understanding-mitigating-spurious-signal-amplification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yongcan Yu, Lingxiao He, Jian Liang, et al.*2026*
229. **[Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-understanding-preventing-entropy-collapse-rlvr/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Huimin Xu, Shuai Zhao, Xiaobao Wu, et al.*2026*
230. **[Understanding Conflicts in Multi-Objective Alignment through Reward Consistency](https://md.research.elamur.ai/free/en/papers/xu-2026-understanding-conflicts-multi-objective-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhihao Xu, Yongqi Tong, Xin Zhang, et al.*2026*
231. **[V-RoLoRA: RLVR-Driven MoE Routing for Steerable Pluralistic Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-v-rolora-rlvr-driven-moe/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Wang, Yaomin Wu, Yinglin Wang, et al.*2026*
232. **[Verifying the Subjective: Structured Multilingual Rewards for Low-Resource Alignment](https://md.research.elamur.ai/free/en/papers/sha-2026-verifying-subjective-structured-multilingual-rewards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiu Sha, Mengxiao Zhu*2026*
233. **[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*
234. **[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*
235. **[When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors](https://md.research.elamur.ai/free/en/papers/yang-2026-when-llms-read-tables-carelessly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuqing Yang, Qi Zhu, Zhen Han, et al.*2026*
236. **[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*
237. **[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*
238. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*
239. **[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*
240. **[Generating Questions Under Discussion with Reinforcement Learning using Ranking and Scoring for Reward and Evaluation](https://md.research.elamur.ai/free/en/papers/han-2025-generating-questions-under-discussion-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kelvin Han, Claire Gardent*2025*
241. [**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/)

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

578 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/saumya-malik/) — Saumya Malik