---
title: "Who cites Tamara Berg"
description: "467 papers of the Elamur Research library cite the works of Tamara Berg, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/tamara-berg/cited-by/"
---
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# Who cites Tamara Berg

534 citations of their works from 467 papers of our library (of the 140,884 whose bibliographies we read) · 54 with a page here, the most cited first · [← Tamara Berg](https://md.research.elamur.ai/free/en/authors/tamara-berg/)

1. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,483 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)
2. [**Improved Baselines with Visual Instruction Tuning**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,557 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/)
3. [**UNITER: UNiversal Image-TExt Representation Learning**Yen-Chun Chen, Linjie Li, Licheng Yu, et al.*2019 · 2,344 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-uniter-universal-image-text-representation/)
4. [**ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks**Jiasen Lu, Dhruv Batra, Devi Parikh, et al.*2019 · 2,217 citations*](https://md.research.elamur.ai/free/en/papers/lu-2019-vilbert-pretraining-task-agnostic-visiolinguistic/)
5. [**Microsoft COCO Captions: Data Collection and Evaluation Server**Xinlei Chen, Hao Fang, Tsung-Yi Lin, et al.*2015 · 1,859 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-microsoft-coco-captions-data-collection/)
6. [**VisualBERT: A Simple and Performant Baseline for Vision and Language**Liunian Harold Li, Mark Yatskar, Da Yin, et al.*2019 · 1,510 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/)
7. [**Generation and Comprehension of Unambiguous Object Descriptions**Junhua Mao, Jonathan Huang, Alexander Toshev, et al.*2015 · 1,358 citations*](https://md.research.elamur.ai/free/en/papers/mao-2015-generation-comprehension-unambiguous-object-descriptions/)
8. [**Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models**Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel*2014 · 1,315 citations*](https://md.research.elamur.ai/free/en/papers/kiros-2014-unifying-visual-semantic-embeddings-multimodal/)
9. [**Modeling Context in Referring Expressions**Licheng Yu, Patrick Poirson, Shan Yang, et al.*2016 · 1,165 citations*](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/)
10. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,105 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
11. [**VL-BERT: Pre-training of Generic Visual-Linguistic Representations**Weijie Su, Xizhou Zhu, Yue Cao, et al.*2019 · 1,008 citations*](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/)
12. [**Qwen2.5-VL Technical Report**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 948 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
13. [**MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/)
14. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 913 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
15. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 819 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
16. [**TVQA: Localized, Compositional Video Question Answering**Jie Lei, Licheng Yu, Mohit Bansal, et al.*2018 · 669 citations*](https://md.research.elamur.ai/free/en/papers/lei-2018-tvqa-localized-compositional-video-question/)
17. [**A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)**Alane Suhr, Stephanie Zhou, Ally Zhang, et al.*2019 · 640 citations*](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/)
18. [**Show and Tell: A Neural Image Caption Generator**Oriol Vinyals, Alexander Toshev, Samy Bengio, et al.*2014 · 606 citations*](https://md.research.elamur.ai/free/en/papers/vinyals-2014-show-tell-neural-image-caption/)
19. [**How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 529 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/)
20. [**Deep Visual-Semantic Alignments for Generating Image Descriptions**Andrej Karpathy, Li Fei-Fei*2014 · 493 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2014-deep-visual-semantic-alignments-generating/)
21. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework**Peng Wang, An Yang, Rui Men, et al.*2022 · 452 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
22. [**MVBench: A Comprehensive Multi-modal Video Understanding Benchmark**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/)
23. [**ShareGPT4V: Improving Large Multi-Modal Models with Better Captions**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/)
24. [**LLaVA-OneVision: Easy Visual Task Transfer**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 440 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
25. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 409 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
26. [**Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 403 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/)
27. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 403 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
28. [**Yi: Open Foundation Models by 01.AI**Alex Young, Bei Chen, Chao Li, et al.*2024 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
29. [**CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2016 · 387 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2016-clevr-diagnostic-dataset-compositional-language/)
30. [**CogVLM: Visual Expert for Pretrained Language Models**Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.*2023 · 373 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/)
31. [**Toward Abstractive Summarization Using Semantic Representations**Fei Liu, Jeffrey Flanigan, Sam Thomson, et al.*2015 · 337 citations*](https://md.research.elamur.ai/free/en/papers/liu-2015-abstractive-summarization-semantic-representations/)
32. [**Qwen3-VL Technical Report**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 330 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/)
33. [**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/)
34. [**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/)
35. [**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/)
36. [**Qwen2.5-Omni Technical Report**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 218 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
37. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 195 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
38. [**Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic**Keqin Chen, Zhao Zhang, Weili Zeng, et al.*2023 · 194 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-shikra-unleashing-multimodal-llm-s/)
39. [**MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning**Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.*2023 · 192 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-minigpt-v2-large-language-model/)
40. [**Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/)
41. [**Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 173 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/)
42. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
43. [**Long-term Recurrent Convolutional Networks for Visual Recognition and Description**Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, et al.*2014 · 142 citations*](https://md.research.elamur.ai/free/en/papers/donahue-2014-long-term-recurrent-convolutional-networks/)
44. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
45. [**GPT-4V(ision) is a Generalist Web Agent, if Grounded**Boyuan Zheng, Boyu Gou, Jihyung Kil, et al.*2024 · 130 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-gpt-4v-ision-generalist-web/)
46. [**Unified Pragmatic Models for Generating and Following Instructions**Daniel Fried, Jacob Andreas, Dan Klein*2018 · 111 citations*](https://md.research.elamur.ai/free/en/papers/fried-2018-unified-pragmatic-models-generating-following/)
47. [**Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/)
48. [**Know What You Don't Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories**Sina Zarrieß, David Schlangen*2019 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zarriess-2019-know-what-you-don-t/)
49. [**Maintaining Common Ground in Dynamic Environments**Takuma Udagawa, Akiko Aizawa*2021 · 13 citations*](https://md.research.elamur.ai/free/en/papers/udagawa-2021-maintaining-common-ground-dynamic-environments/)
50. [**This One or That One? A Study on Accessibility via Demonstratives with Multimodal Large Language Models**Yu Wang, Emmanuele Chersoni, Chu-Ren Huang*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2026-this-one-or-that-one/)
51. [**Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach**Hieu Le, Taufiq Daryanto, Fabian Zhafransyah, et al.*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/le-2022-referring-expressions-rational-speech-act/)
52. [**Multi-modal, Multi-task, Multi-criteria Automatic Evaluation with Vision Language Models**Masanari Oi, Masahiro Kaneko, Naoaki Okazaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/oi-2026-multi-modal-multi-task-multi/)
53. [**Frame2KG: A Benchmark and Evaluation Toolkit for Interpretable Frame-to-Graph Generation**Lewis N. Watson, Carl Strathearn, Kenny Mitchell, et al.*2026*](https://md.research.elamur.ai/free/en/papers/watson-2026-frame2kg-benchmark-evaluation-toolkit-interpretable/)
54. [**Survey on Vision-language Pre-training (视觉语言预训练综述)**Jiong Yin (殷炯), Zhedong Zhang (张哲东), Yuhan Gao (高宇涵), et al.*2022*](https://md.research.elamur.ai/free/en/papers/yin-2022-vision-language-pre/)

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

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