---
title: "Who cites Urvashi Khandelwal — page 3 — 3,832 citing papers"
description: "3,832 papers of the Elamur Research library cite the works of Urvashi Khandelwal, found in their bibliographies · page 3 of 9 · 201–300; the…"
canonical: "https://research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/3/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/3/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Urvashi Khandelwal](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/) / [cited by](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/) / page 3

# Who cites Urvashi Khandelwal

4,013 citations of their works from 3,832 papers of our library (of the 149,439 whose bibliographies we read) · 851 with a page here, the most cited first · page 3 of 9 · 201–300 · [← Urvashi Khandelwal](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/)

[← prev](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/2/) **3** [4](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/4/) … [9](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/9/) [next →](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/4/)

201. **[The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/kirk-2024-prism-alignment-dataset-participatory-representative/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.*2024 · 133 citations*
202. **[Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion](https://md.research.elamur.ai/free/en/papers/shuster-2022-language-models-that-seek-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, et al.*2022 · 132 citations*
203. **[Analyzing Transformers in Embedding Space](https://md.research.elamur.ai/free/en/papers/dar-2023-analyzing-transformers-embedding-space/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guy Dar, Mor Geva, Ankit Gupta, et al.*2023 · 130 citations*
204. [**Retrieval meets Long Context Large Language Models arXiv:2310.03025**Peng Xu, Wei Ping, Xianchao Wu, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-retrieval-meets-long-context-large/)
205. **[Efficient Nearest Neighbor Language Models](https://md.research.elamur.ai/free/en/papers/he-2021-efficient-nearest-neighbor-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick*2021 · 130 citations*
206. **[Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 129 citations*
207. **[OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement](https://md.research.elamur.ai/free/en/papers/zheng-2024-opencodeinterpreter-integrating-code-generation-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Zheng, Ge Zhang, Tianhao Shen, et al.*2024 · 129 citations*
208. **[UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model](https://md.research.elamur.ai/free/en/papers/ye-2023-ureader-universal-ocr-free-visually/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiabo Ye, Anwen Hu, Haiyang Xu, et al.*2023 · 129 citations*
209. [**LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models arXiv:2407.07895**Feng Li, Renrui Zhang, Hao Zhang, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-next-interleave-tackling-multi/)
210. **[SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding](https://md.research.elamur.ai/free/en/papers/xu-2024-safedecoding-defending-against-jailbreak-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 127 citations*
211. [**Function Vectors in Large Language Models arXiv:2310.15213**Eric Todd, Millicent L. Li, Arnab Sen Sharma, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/todd-2023-function-vectors-large-language-models/)
212. **[InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 126 citations*
213. **[LM vs LM: Detecting Factual Errors via Cross Examination](https://md.research.elamur.ai/free/en/papers/cohen-2023-lm-vs-lm-detecting-factual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Roi Cohen, May Hamri, Mor Geva, et al.*2023 · 126 citations*
214. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
215. **[Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-mini-gemini-mining-potential-multi/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Yanwei Li, Yuechen Zhang, Chengyao Wang, et al.*2024 · 123 citations*
216. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
217. [**Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation**Atticus Geiger, Kyle Richardson, Christopher Potts*2020 · 123 citations*](https://md.research.elamur.ai/free/en/papers/geiger-2020-neural-natural-language-inference-models/)
218. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
219. **[DePlot: One-shot visual language reasoning by plot-to-table translation](https://md.research.elamur.ai/free/en/papers/liu-2023-deplot-one-shot-visual-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fangyu Liu, Julian Eisenschlos, Francesco Piccinno, et al.*2023 · 122 citations*
220. **[UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 121 citations*
221. **[AlphaMath Almost Zero: Process Supervision without Process](https://md.research.elamur.ai/free/en/papers/chen-2024-alphamath-almost-zero-process-supervision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guoxin Chen, Minpeng Liao, Chengxi Li, et al.*2024 · 120 citations*
222. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
223. **[Adaptive Nearest Neighbor Machine Translation](https://md.research.elamur.ai/free/en/papers/zheng-2021-adaptive-nearest-neighbor-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Zheng, Zhirui Zhang, Junliang Guo, et al.*2021 · 120 citations*
224. **[Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/wu-2021-good-misconceived-reasons-empirical-revisiting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyong Wu, Lingpeng Kong, Wei Bi, et al.*2021 · 120 citations*
225. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
226. **[CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-charxiv-charting-gaps-realistic-chart/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zirui Wang, Mengzhou Xia, Luxi He, et al.*2024 · 119 citations*
227. [**LLaVA-Video: Video Instruction Tuning With Synthetic Data arXiv:2410.02713**Yuanhan Zhang, Jinming Wu, Wei Li, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-llava-video-video-instruction-tuning/)
228. **[SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 119 citations*
229. [**Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks arXiv:2404.02151**Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/andriushchenko-2024-jailbreaking-leading-safety-aligned-llms/)
230. [**VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs arXiv:2406.07476**Zesen Cheng, Sicong Leng, Hang Zhang, et al.*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-videollama-2-advancing-spatial-temporal/)
231. **[Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hao Shao, Shengju Qian, Han Xiao, et al.*2024 · 117 citations*
232. **[How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN](https://md.research.elamur.ai/free/en/papers/mccoy-2023-how-much-do-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.*2023 · 117 citations*
233. [**Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation arXiv:2212.07981**Yixin Liu, Alexander R. Fabbri, Pengfei Liu, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-revisiting-gold-standard-grounding-summarization/)
234. [**Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model arXiv:1912.09637**Wenhan Xiong, Jingfei Du, William Yang Wang, et al.*2019 · 117 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2019-pretrained-encyclopedia-weakly-supervised-knowledge/)
235. [**Mixture-of-Agents Enhances Large Language Model Capabilities arXiv:2406.04692**Junlin Wang, Jue Wang, Ben Athiwaratkun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mixture-agents-enhances-large/)
236. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
237. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
238. [**Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2 arXiv:2408.05147**Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/lieberum-2024-gemma-scope-open-sparse-autoencoders/)
239. [**RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation arXiv:2310.04408**Fangyuan Xu, Weijia Shi, Eunsol Choi*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/)
240. **[MoEfication: Transformer Feed-forward Layers are Mixtures of Experts](https://md.research.elamur.ai/free/en/papers/zhang-2022-moefication-transformer-feed-forward-layers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengyan Zhang, Yankai Lin, Zhiyuan Liu, et al.*2022 · 115 citations*
241. [**Break the Sequential Dependency of LLM Inference Using Lookahead Decoding arXiv:2402.02057**Yichao Fu, Peter Bailis, Ion Stoica, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-break-sequential-dependency-llm-inference/)
242. [**DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads arXiv:2410.10819**Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-duoattention-efficient-long-context-llm/)
243. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
244. [**Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling arXiv:2501.17811**Xiaokang Chen, Zhiyu Wu, Xingchao Liu, et al.*2025 · 112 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-janus-pro-unified-multimodal/)
245. **[Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/wu-2024-janus-decoupling-visual-encoding/) [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/)**Chengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.*2024 · 112 citations*
246. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs arXiv:2410.18451**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 112 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/)
247. **[mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2024-mplug-docowl-1-5-unified/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anwen Hu, Haiyang Xu, Jiabo Ye, et al.*2024 · 111 citations*
248. [**Orca-Math: Unlocking the potential of SLMs in Grade School Math arXiv:2402.14830**Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2024-orca-math-unlocking-potential-slms/)
249. [**ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models arXiv:2404.07738**Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/baek-2024-researchagent-iterative-research-idea/)
250. [**RLHF Workflow: From Reward Modeling to Online RLHF arXiv:2405.07863**Hanze Dong, Wei Xiong, Bo Pang, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-rlhf-workflow-reward-modeling-online/)
251. **[Unlimiformer: Long-Range Transformers with Unlimited Length Input](https://md.research.elamur.ai/free/en/papers/bertsch-2023-unlimiformer-long-range-transformers-unlimited/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Amanda Bertsch, Uri Alon, Graham Neubig, et al.*2023 · 111 citations*
252. [**Benchmarking Machine Translation with Cultural Awareness arXiv:2305.14328**Binwei Yao, Ming Jiang, Tara Bobinac, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-benchmarking-machine-translation-cultural-awareness/)
253. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
254. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
255. **[Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qineng Wang, Zihao Wang, Ying Su, et al.*2024 · 107 citations*
256. **[Understanding Learning Dynamics Of Language Models with SVCCA](https://md.research.elamur.ai/free/en/papers/saphra-2019-understanding-learning-dynamics-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Naomi Saphra, Adam Lopez*2019 · 107 citations*
257. **[Learning to Retrieve In-Context Examples for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-learning-retrieve-context-examples-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Liang Wang, Nan Yang, Furu Wei*2024 · 106 citations*
258. **[Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/dankers-2022-can-transformer-be-too-compositional/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Verna Dankers, Christopher Lucas, Ivan Titov*2022 · 106 citations*
259. **[CDLM: Cross-Document Language Modeling](https://md.research.elamur.ai/free/en/papers/caciularu-2021-cdlm-cross-document-language-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Avi Caciularu, Arman Cohan, Iz Beltagy, et al.*2021 · 106 citations*
260. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
261. [**Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention USENIX ATC 2024**Bin Gao, Zhuomin He, Puru Sharma, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-cost-efficient-large-language-model/)
262. **[Disentangling Length from Quality in Direct Preference Optimization](https://md.research.elamur.ai/free/en/papers/park-2024-disentangling-length-quality-direct-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ryan Park, Rafael Rafailov, Stefano Ermon, et al.*2024 · 105 citations*
263. [**REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization arXiv:2501.03262**Jian Hu, Jason Klein Liu, Haotian Xu, et al.*2025 · 104 citations*](https://md.research.elamur.ai/free/en/papers/hu-2025-reinforce-stabilizing-critic-free-policy/)
264. **[Chain of Agents: Large Language Models Collaborating on Long-Context Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2024-chain-agents-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yusen Zhang, Ruoxi Sun, Yanfei Chen, et al.*2024 · 104 citations*
265. **[Towards Measuring and Modeling “Culture” in LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/adilazuarda-2024-measuring-modeling-culture-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.*2024 · 103 citations*
266. **[How do Large Language Models Handle Multilingualism?](https://md.research.elamur.ai/free/en/papers/zhao-2024-large-language-models-handle-multilingualism/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yiran Zhao, Wenxuan Zhang, Guizhen Chen, et al.*2024 · 102 citations*
267. [**The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models arXiv:2505.22617**Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-entropy-mechanism-reinforcement-learning-reasoning/)
268. **[A Careful Examination of Large Language Model Performance on Grade School Arithmetic](https://md.research.elamur.ai/free/en/papers/zhang-2024-careful-examination-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugh Zhang, Jeff Da, Dean Lee, et al.*2024 · 101 citations*
269. [**Debating with More Persuasive LLMs Leads to More Truthful Answers arXiv:2402.06782**Akbir Khan, John Hughes, Dan Valentine, et al.*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/khan-2024-debating-more-persuasive-llms-leads/)
270. **[Do Long-Range Language Models Actually Use Long-Range Context?](https://md.research.elamur.ai/free/en/papers/sun-2021-do-long-range-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke, et al.*2021 · 101 citations*
271. **[Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2024-unsupervised-real-time-hallucination-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weihang Su, Changyue Wang, Qingyao Ai, et al.*2024 · 99 citations*
272. [**World Model on Million-Length Video And Language With Blockwise RingAttention arXiv:2402.08268**Hao Liu, Wilson Yan, Matei Zaharia, et al.*2024 · 99 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-world-model-million-length-video/)
273. [**ChartLlama: A Multimodal LLM for Chart Understanding and Generation arXiv:2311.16483**Yucheng Han, Chi Zhang, Xin Chen, et al.*2023 · 99 citations*](https://md.research.elamur.ai/free/en/papers/han-2023-chartllama-multimodal-llm-chart-understanding/)
274. [**LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding arXiv:2306.17107**Yanzhe Zhang, Ruiyi Zhang, Jiuxiang Gu, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llavar-enhanced-visual-instruction-tuning/)
275. [**Safety Alignment Should Be Made More Than Just a Few Tokens Deep arXiv:2406.05946**Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-safety-alignment-should-made-more/)
276. **[Inseq: An Interpretability Toolkit for Sequence Generation Models](https://md.research.elamur.ai/free/en/papers/sarti-2023-inseq-interpretability-toolkit-sequence-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gabriele Sarti, Nils Feldhus, Ludwig Sickert, et al.*2023 · 97 citations*
277. [**Are Transformers universal approximators of sequence-to-sequence functions? arXiv:1912.10077**Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, et al.*2019 · 97 citations*](https://md.research.elamur.ai/free/en/papers/yun-2019-transformers-universal-approximators-sequence-sequence/)
278. **[MAmmoTH2: Scaling Instructions from the Web](https://md.research.elamur.ai/free/en/papers/yue-2024-mammoth2-scaling-instructions-web/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiang Yue, Tuney Zheng, Ge Zhang, et al.*2024 · 96 citations*
279. [**The Platonic Representation Hypothesis arXiv:2405.07987**Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/huh-2024-platonic-representation-hypothesis/)
280. **[Probing Across Time: What Does RoBERTa Know and When?](https://md.research.elamur.ai/free/en/papers/liu-2021-probing-across-time-what-does/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leo Z. Liu, Yizhong Wang, Jungo Kasai, et al.*2021 · 96 citations*
281. [**Multi-Agent Collaboration Mechanisms: A Survey of LLMs arXiv:2501.06322**Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, et al.*2025 · 95 citations*](https://md.research.elamur.ai/free/en/papers/tran-2025-multi-agent-collaboration-mechanisms/)
282. **[LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models](https://md.research.elamur.ai/free/en/papers/han-2024-lm-infinite-zero-shot-extreme/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chi Han, Qifan Wang, Hao Peng, et al.*2024 · 95 citations*
283. [**Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation arXiv:2302.07856**Marjan Ghazvininejad, Hila Gonen, Luke Zettlemoyer*2023 · 95 citations*](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2023-dictionary-based-phrase-level-prompting/)
284. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
285. **[Aligning Language Models to User Opinions](https://md.research.elamur.ai/free/en/papers/hwang-2023-aligning-language-models-user-opinions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**EunJeong Hwang, Bodhisattwa Majumder, Niket Tandon*2023 · 93 citations*
286. **[MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations](https://md.research.elamur.ai/free/en/papers/ma-2024-mmlongbench-doc-benchmarking-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Ma, Yuhang Zang, Liangyu Chen, et al.*2024 · 92 citations*
287. **[Medical Graph RAG: Evidence-based Medical Large Language Model via Graph Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wu-2025-medical-graph-rag-evidence-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junde Wu, Jiayuan Zhu, Yunli Qi, et al.*2025 · 91 citations*
288. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/)
289. **[CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark](https://md.research.elamur.ai/free/en/papers/romero-2024-cvqa-culturally-diverse-multilingual-visual/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo, et al.*2024 · 90 citations*
290. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)
291. **[Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey](https://md.research.elamur.ai/free/en/papers/kumar-2023-language-generation-models-can-cause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.*2023 · 90 citations*
292. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
293. [**SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines arXiv:2502.14739**M-A-P Team, Xinrun Du, Yifan Yao, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-supergpqa-scaling-llm-evaluation-across/)
294. [**ReTool: Reinforcement Learning for Strategic Tool Use in LLMs arXiv:2504.11536**Jiazhan Feng, Shijue Huang, Xingwei Qu, et al.*2025 · 88 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/)
295. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations*
296. [**Massive Activations in Large Language Models arXiv:2402.17762**Mingjie Sun, Xinlei Chen, J. Zico Kolter, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-massive-activations-large-language-models/)
297. **[Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-not-all-experts-are-equal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xudong Lu, Qi Liu, Yuhui Xu, et al.*2024 · 88 citations*
298. **[Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement](https://md.research.elamur.ai/free/en/papers/xu-2024-pride-prejudice-llm-amplifies-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenda Xu, Guanglei Zhu, Xuandong Zhao, et al.*2024 · 88 citations*
299. [**Landmark Attention: Random-Access Infinite Context Length for Transformers arXiv:2305.16300**Amirkeivan Mohtashami, Martin Jaggi*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mohtashami-2023-landmark-attention-random-access-infinite/)
300. [**Learning to Filter Context for Retrieval-Augmented Generation arXiv:2311.08377**Zhiruo Wang, Jun Araki, Zhengbao Jiang, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-learning-filter-context-retrieval-augmented/)

[← prev](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/2/) **3** [4](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/4/) … [9](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/9/) [next →](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/cited-by/page/4/)

- [← back to](https://md.research.elamur.ai/free/en/authors/urvashi-khandelwal/) — Urvashi Khandelwal
