---
title: "Computer Vision and Pattern Recognition — papers, page 6"
description: "Computer Vision and Pattern Recognition: 1,282 papers of the Elamur Research library · page 6 of 14 · 426–525, the most cited first — our summary of each…"
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---
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# 👁️ Computer Vision and Pattern Recognition

1,282 papers · page 6 of 14 · 426–525 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Computer Vision and Pattern Recognition is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Multimodal Machine Learning Applications», «Advanced Neural Network Applications», «Handwritten Text Recognition Techniques».

## Papers

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426. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 328 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
427. [**HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 326 citations*](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/)
428. [**Compressive Transformers for Long-Range Sequence Modelling**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 326 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
429. [**Representation Learning: A Review and New Perspectives**Yoshua Bengio, Aaron Courville, Pascal Vincent*2012 · 325 citations*](https://md.research.elamur.ai/free/en/papers/bengio-2012-representation-learning-review-new-perspectives/)
430. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 324 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
431. [**Are Emergent Abilities of Large Language Models a Mirage?**Rylan Schaeffer, Brando Miranda, Sanmi Koyejo*2023 · 323 citations*](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-emergent-abilities-large-language-models/)
432. [**Language Is Not All You Need: Aligning Perception with Language Models**Shaohan Huang, Li Dong, Wenhui Wang, et al.*2023 · 322 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-language-all-need-aligning-perception/)
433. [**MM-LLMs: Recent Advances in MultiModal Large Language Models**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 318 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/)
434. [**Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding**Sicong Leng, Hang Zhang, Guanzheng Chen, et al.*2023 · 317 citations*](https://md.research.elamur.ai/free/en/papers/leng-2023-mitigating-object-hallucinations-large-vision/)
435. [**Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models**Chenfei Wu, Shengming Yin, Weizhen Qi, et al.*2023 · 317 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-visual-chatgpt-talking-drawing-editing/)
436. [**How many data points is a prompt worth?**Teven Le Scao, Alexander Rush*2021 · 316 citations*](https://md.research.elamur.ai/free/en/papers/scao-2021-how-many-data-points-is/)
437. [**LightRAG: Simple and Fast Retrieval-Augmented Generation**Zirui Guo, Lianghao Xia, Yanhua Yu, et al.*2024 · 315 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-lightrag-simple-fast-retrieval-augmented/)
438. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
439. [**LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion**Dongfu Jiang, Xiang Ren, Bill Yuchen Lin*2023 · 314 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-llm-blender-ensembling-large-language/)
440. [**Double Graph Based Reasoning for Document-level Relation Extraction**Shuang Zeng, Runxin Xu, Baobao Chang, et al.*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2020-double-graph-based-reasoning-document/)
441. [**Neural Natural Language Inference Models Enhanced with External Knowledge**Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, et al.*2018 · 314 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-neural-natural-language-inference-models/)
442. [**Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models**Yanzhao Zhang, Mingxin Li, Dingkun Long, et al.*2025 · 313 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-qwen3-embedding-advancing-text/)
443. [**Multi-hop Reading Comprehension through Question Decomposition and Rescoring**Sewon Min, Victor Zhong, Luke Zettlemoyer, et al.*2019 · 306 citations*](https://md.research.elamur.ai/free/en/papers/min-2019-multi-hop-reading-comprehension-through/)
444. [**Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense**Kalpesh Krishna, Yixiao Song, Marzena Karpinska, et al.*2023 · 304 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2023-paraphrasing-evades-detectors-ai-generated/)
445. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 304 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
446. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 303 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
447. [**ZeRO-Offload: Democratizing Billion-Scale Model Training**Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.*2021 · 303 citations*](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/)
448. [**Can AI-Generated Text be Reliably Detected?**Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al.*2023 · 302 citations*](https://md.research.elamur.ai/free/en/papers/sadasivan-2023-ai-generated-text-reliably-detected/)
449. [**Large Language Models are Better Reasoners with Self-Verification**Yixuan Weng, Minjun Zhu, Fei Xia, et al.*2023 · 302 citations*](https://md.research.elamur.ai/free/en/papers/weng-2023-large-language-models-are-better/)
450. [**ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers**Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-zeroquant-efficient-affordable-post-training/)
451. [**Learning Named Entity Tagger using Domain-Specific Dictionary**Jingbo Shang, Liyuan Liu, Xiaotao Gu, et al.*2018 · 301 citations*](https://md.research.elamur.ai/free/en/papers/shang-2018-learning-named-entity-tagger-domain/)
452. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
453. [**Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation**Ning Dai, Jianze Liang, Xipeng Qiu, et al.*2019 · 300 citations*](https://md.research.elamur.ai/free/en/papers/dai-2019-style-transformer-unpaired-text-style/)
454. [**InternLM2 Technical Report**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 299 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
455. [**Chain-of-Verification Reduces Hallucination in Large Language Models**Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.*2023 · 299 citations*](https://md.research.elamur.ai/free/en/papers/dhuliawala-2023-chain-verification-reduces-hallucination-large/)
456. [**UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning**Wei Li, Can Gao, Guocheng Niu, et al.*2021 · 299 citations*](https://md.research.elamur.ai/free/en/papers/li-2021-unimo-unified-modal-understanding-generation/)
457. [**Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network**Sunil Kumar Sahu, Fenia Christopoulou, Makoto Miwa, et al.*2019 · 299 citations*](https://md.research.elamur.ai/free/en/papers/sahu-2019-inter-sentence-relation-extraction-document/)
458. [**Entity Linking via Joint Encoding of Types, Descriptions, and Context**Nitish Gupta, Sameer Singh, Dan Roth*2017 · 298 citations*](https://md.research.elamur.ai/free/en/papers/gupta-2017-entity-linking-joint-encoding-types/)
459. [**Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs**Shengbang Tong, Zhuang Liu, Yuexiang Zhai, et al.*2024 · 297 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-eyes-wide-shut-exploring-visual/)
460. [**Multimodal Chain-of-Thought Reasoning in Language Models**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-multimodal-chain-thought-reasoning-language/)
461. [**OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/)
462. [**Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning**Pengda Qin, Weiran Xu, William Yang Wang*2018 · 297 citations*](https://md.research.elamur.ai/free/en/papers/qin-2018-robust-distant-supervision-relation-extraction/)
463. [**Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering**Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, et al.*2020 · 296 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-scalable-multi-hop-relational-reasoning/)
464. [**AdapterDrop: On the Efficiency of Adapters in Transformers**Andreas Rücklé, Gregor Geigle, Max Glockner, et al.*2021 · 295 citations*](https://md.research.elamur.ai/free/en/papers/ruckle-2021-adapterdrop-efficiency-adapters-transformers/)
465. [**Entity-Based Knowledge Conflicts in Question Answering**Shayne Longpre, Kartik Perisetla, Anthony Chen, et al.*2021 · 295 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/)
466. [**KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization**Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, et al.*2024 · 293 citations*](https://md.research.elamur.ai/free/en/papers/hooper-2024-kvquant-towards-10-million-context/)
467. [**HAT: Hardware-Aware Transformers for Efficient Natural Language Processing**Hanrui Wang, Zhanghao Wu, Zhijian Liu, et al.*2020 · 290 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-hat-hardware-aware-transformers-efficient/)
468. [**Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 289 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/)
469. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
470. [**GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification**Jie Zhou, Xu Han, Cheng Yang, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2019-gear-graph-based-evidence-aggregating/)
471. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 287 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
472. [**Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders**Jue Wang, Wei Lu*2020 · 287 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/)
473. [**Learning Grounded Meaning Representations with Autoencoders**Carina Silberer, Mirella Lapata*2014 · 287 citations*](https://md.research.elamur.ai/free/en/papers/silberer-2014-learning-grounded-meaning-representations-autoencoders/)
474. [**Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca**Yiming Cui, Ziqing Yang, Xin Yao*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-efficient-effective-text-encoding-chinese/)
475. [**Text Generation from Knowledge Graphs with Graph Transformers**Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, et al.*2019 · 286 citations*](https://md.research.elamur.ai/free/en/papers/kedziorski-2019-text-generation-knowledge-graphs-graph/)
476. [**ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning**Weihao Yu, Zihang Jiang, Yanfei Dong, et al.*2020 · 285 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-reclor-reading-comprehension-dataset-requiring/)
477. [**Constructing Datasets for Multi-hop Reading Comprehension Across Documents**Johannes Welbl, Pontus Stenetorp, Sebastian Riedel*2018 · 284 citations*](https://md.research.elamur.ai/free/en/papers/welbl-2018-constructing-datasets-multi-hop-reading/)
478. [**Spelling Error Correction with Soft-Masked BERT**Shaohua Zhang, Haoran Huang, Jicong Liu, et al.*2020 · 283 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-spelling-error-correction-soft-masked/)
479. [**MEGA: Multilingual Evaluation of Generative AI**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 282 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
480. [**Fine-grained Fact Verification with Kernel Graph Attention Network**Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.*2020 · 282 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/)
481. [**Multi-Sentence Argument Linking**Seth Ebner, Patrick Xia, Ryan Culkin, et al.*2020 · 281 citations*](https://md.research.elamur.ai/free/en/papers/ebner-2020-multi-sentence-argument-linking/)
482. [**AlignScore: Evaluating Factual Consistency with A Unified Alignment Function**Yuheng Zha, Yichi Yang, Ruichen Li, et al.*2023 · 280 citations*](https://md.research.elamur.ai/free/en/papers/zha-2023-alignscore-evaluating-factual-consistency-unified/)
483. [**Otter: A Multi-Modal Model with In-Context Instruction Tuning**Bo Li, Yuanhan Zhang, Liangyu Chen, et al.*2023 · 280 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-otter-multi-modal-model-context/)
484. [**Generate rather than Retrieve: Large Language Models are Strong Context Generators**Wenhao Yu, Dan Iter, Shuohang Wang, et al.*2022 · 280 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-generate-rather-than-retrieve-large/)
485. [**Guided Open Vocabulary Image Captioning with Constrained Beam Search**Peter Anderson, Basura Fernando, Mark Johnson, et al.*2017 · 279 citations*](https://md.research.elamur.ai/free/en/papers/anderson-2017-guided-open-vocabulary-image-captioning/)
486. [**A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions**Junchao Wu, Shu Yang, Runzhe Zhan, et al.*2025 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-survey-llm-generated-text-detection/)
487. [**An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models**Liang Chen, Haozhe Zhao, Tianyu Liu, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-image-worth-1-2-tokens/)
488. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
489. [**ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT**Xiang Wei; Xingyu Cui; Ning Cheng; Xiaobin Wang; Xin Zhang; Shen Huang; Pengjun Xie; Jinan Xu; Yufeng Chen; Meishan Zhang; Yong Jiang;, Wenjuan Han*2023 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-chatie-zero-shot-information-extraction/)
490. [**Large Dual Encoders Are Generalizable Retrievers**Jianmo Ni, Chen Qu, Jing Lu, et al.*2021 · 276 citations*](https://md.research.elamur.ai/free/en/papers/ni-2021-large-dual-encoders-generalizable-retrievers/)
491. [**LLM-QAT: Data-Free Quantization Aware Training for Large Language Models**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 275 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/)
492. [**Applying Many-to-Many Alignments and Hidden Markov Models to Letter-to-Phoneme Conversion**Sittichai Jiampojamarn, Grzegorz Kondrak, Tarek Sherif*2007 · 274 citations*](https://md.research.elamur.ai/free/en/papers/jiampojamarn-2007-applying-many-many-alignments-hidden/)
493. [**Kosmos-2: Grounding Multimodal Large Language Models to the World**Zhiliang Peng, Wenhui Wang, Li Dong, et al.*2023 · 272 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/)
494. [**Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering**Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.*2019 · 272 citations*](https://md.research.elamur.ai/free/en/papers/asai-2019-learning-retrieve-reasoning-paths-over/)
495. [**Corrective Retrieval Augmented Generation**Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/yan-2024-corrective-retrieval-augmented-generation/)
496. [**Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads**Tianle Cai, Yuhong Li, Zhengyang Geng, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/)
497. [**Adaptively Sparse Transformers**Gonçalo M. Correia, Vlad Niculae, André F. T. Martins*2019 · 271 citations*](https://md.research.elamur.ai/free/en/papers/correia-2019-adaptively-sparse-transformers/)
498. [**Reducing Activation Recomputation in Large Transformer Models**Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.*2022 · 270 citations*](https://md.research.elamur.ai/free/en/papers/korthikanti-2022-reducing-activation-recomputation-large-transformer/)
499. [**Minimum Cut Model for Spoken Lecture Segmentation**Igor Malioutov, Regina Barzilay*2006 · 270 citations*](https://md.research.elamur.ai/free/en/papers/malioutov-2006-minimum-cut-model-spoken-lecture/)
500. [**Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters**Boshi Wang, Sewon Min, Xiang Deng, et al.*2023 · 269 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-understanding-chain-thought-prompting-empirical/)
501. [**Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models**Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, et al.*2016 · 269 citations*](https://md.research.elamur.ai/free/en/papers/vijayakumar-2016-diverse-beam-search-decoding-diverse/)
502. [**Injecting Numerical Reasoning Skills into Language Models**Mor Geva, Ankit Gupta, Jonathan Berant*2020 · 268 citations*](https://md.research.elamur.ai/free/en/papers/geva-2020-injecting-numerical-reasoning-skills-into/)
503. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
504. [**CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review**Dan Hendrycks, Collin Burns, Anya Chen, et al.*2021 · 267 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-cuad-expert-annotated-nlp-dataset/)
505. [**A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer**Fuli Luo, Peng Li, Jie Zhou, et al.*2019 · 266 citations*](https://md.research.elamur.ai/free/en/papers/luo-2019-dual-reinforcement-learning-framework-unsupervised/)
506. [**Are We on the Right Way for Evaluating Large Vision-Language Models?**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2024 · 263 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-right-way-evaluating-large-vision/)
507. [**DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models**Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)
508. [**Condenser: a Pre-training Architecture for Dense Retrieval**Luyu Gao, Jamie Callan*2021 · 261 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-condenser-pre-training-architecture-dense/)
509. [**SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor!**Chhavi Sharma, Deepesh Bhageria, William Scott, et al.*2020 · 260 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2020-semeval-2020-task-8-memotion/)
510. [**Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge**Todor Mihaylov, Anette Frank*2018 · 260 citations*](https://md.research.elamur.ai/free/en/papers/mihaylov-2018-knowledgeable-reader-enhancing-cloze-style/)
511. [**A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification**Ye Zhang, Byron Wallace*2017 · 259 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-sensitivity-analysis-practitioners-guide-convolutional/)
512. [**UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification**Andreas Hanselowski, Hao Zhang, Zile Li, et al.*2018 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hanselowski-2018-ukp-athene-multi-sentence-textual/)
513. [**Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions**Pouya Pezeshkpour, Estevam Hruschka*2023 · 256 citations*](https://md.research.elamur.ai/free/en/papers/pezeshkpour-2023-large-language-models-sensitivity-order/)
514. [**DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale**Samyam Rajbhandari, Conglong Li, Zhewei Yao, et al.*2022 · 255 citations*](https://md.research.elamur.ai/free/en/papers/rajbhandari-2022-deepspeed-moe-advancing-mixture-experts/)
515. [**Learning from Context or Names? An Empirical Study on Neural Relation Extraction**Hao Peng, Tianyu Gao, Xu Han, et al.*2020 · 255 citations*](https://md.research.elamur.ai/free/en/papers/peng-2020-learning-context-or-names-empirical/)
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