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The rapid advancement of Vision-Language Models (VLMs) has significantly advanced the development of Embodied Question Answering (EQA), enhancing agents' abilities in language understanding and reasoning within complex and realistic scenarios.
Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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Multi-target embodied question answering
Licheng Yu, Xinlei Chen, Georgia Gkioxari, Mohit Bansal, Tamara L Berg, and Dhruv Batra · 2019
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The eu ai act: a summary of its significance and scope
Lilian Edwards · 2021
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Sqa3d: Situated question answering in 3d scenes
Xiaojian Ma, Silong Yong, Zilong Zheng, Qing Li, Yitao Liang, Song-Chun Zhu, and Siyuan Huang · 2022
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Dataset shift in machine learning
Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer, and Neil D Lawrence · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Activelab: Active learning with re-labeling by multiple annotators
Hui Wen Goh and Jonas Mueller · 2023
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Evaluating object hallucination in large vision-language models
Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Wayne Xin Zhao, and Ji-Rong Wen · 2023
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Robust-eqa: robust learning for embodied question answering with noisy labels
Haonan Luo, Guosheng Lin, Fumin Shen, Xingguo Huang, Yazhou Yao, and Hengtao Shen · 2023
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Prompting large language models with answer heuristics for knowledge-based visual question answering
Zhenwei Shao, Zhou Yu, Meng Wang, and Jun Yu · 2023
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Learning visual question answering on controlled semantic noisy labels
Haonan Zhang, Pengpeng Zeng, Yuxuan Hu, Jin Qian, Jingkuan Song, and Lianli Gao · 2023
Cited alongside, same era.
S-eqa: Tackling situational queries in embodied question answering
Vishnu Sashank Dorbala, Prasoon Goyal, Robinson Piramuthu, Michael Johnston, Reza Ghanadhan, and Dinesh Manocha · 2024
Cited alongside, same era.
Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models
Tianrui Guan, Fuxiao Liu, Xiyang Wu, Ruiqi Xian, Zongxia Li, Xiaoyu Liu, Xijun Wang, Lichang Chen, Furong Huang, Yaser Yacoob, et al · 2024
Cited alongside, same era.
Detecting and preventing hallucinations in large vision language models
Anisha Gunjal, Jihan Yin, and Erhan Bas · 2024
Cited alongside, same era.
Quantifying the uncertainty of llm hallucination spreading in complex adaptive social networks
Guozhi Hao, Jun Wu, Qianqian Pan, and Rosario Morello · 2024
Explore until confident: Efficient exploration for embodied question answering
Allen Z Ren, Jaden Clark, Anushri Dixit, Masha Itkina, Anirudha Majumdar, and Dorsa Sadigh · 2024
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Adaptive integration of partial label learning and negative learning for enhanced noisy label learning
Mengmeng Sheng, Zeren Sun, Zhenhuang Cai, Tao Chen, Yichao Zhou, and Yazhou Yao · 2024
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Mind the error! detection and localization of instruction errors in vision-and-language navigation
Francesco Taioli, Stefano Rosa, Alberto Castellini, Lorenzo Natale, Alessio Del Bue, Alessandro Farinelli, Marco Cristani, and Yiming Wang · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei, Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al · 2024
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Cited alongside, same era.
Hallucination detection in llm-enriched product listings
Ling Jiang, Keer Jiang, Xiaoyu Chu, Saaransh Gulati, and Pulkit Garg · 2024
Cited alongside, same era.
Prismatic vlms: Investigating the design space of visually-conditioned language models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, and Dorsa Sadigh · 2024
Cited alongside, same era.
Mitigating object hallucinations in large vision-language models through visual contrastive decoding
Sicong Leng, Hang Zhang, Guanzheng Chen, Xin Li, Shijian Lu, Chunyan Miao, and Lidong Bing · 2024
Cited alongside, same era.
How to configure good in-context sequence for visual question answering
Li Li, Jiawei Peng, Huiyi Chen, Chongyang Gao, and Xu Yang · 2024
Cited alongside, same era.
Openeqa: Embodied question answering in the era of foundation models
Arjun Majumdar, Anurag Ajay, Xiaohan Zhang, Pranav Putta, Sriram Yenamandra, Mikael Henaff, Sneha Silwal, Paul Mcvay, Oleksandr Maksymets, Sergio Arnaud, et al · 2024
Cited alongside, same era.
Embodied question answering
Abhishek Das, Samyak Datta, Georgia Gkioxari, Stefan Lee, Devi Parikh, and Dhruv Batra
Cited in the paper.
Neural modular control for embodied question answering
Abhishek Das, Georgia Gkioxari, Stefan Lee, Devi Parikh, and Dhruv Batra
Cited in the paper.
Unlocking the power of open set: A new perspective for open-set noisy label learning
Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li, Sheng-Jun Huang, and Songcan Chen · 2024
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Hallucidoctor: Mitigating hallucinatory toxicity in visual instruction data
Qifan Yu, Juncheng Li, Longhui Wei, Liang Pang, Wentao Ye, Bosheng Qin, Siliang Tang, Qi Tian, and Yueting Zhuang · 2024
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Early stopping against label noise without validation data
Suqin Yuan, Lei Feng, and Tongliang Liu · 2024
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Badlabel: A robust perspective on evaluating and enhancing label-noise learning
Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, and Masashi Sugiyama · 2024
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Dissecting dissonance: Benchmarking large multimodal models against self-contradictory instructions
Jin Gao, Lei Gan, Yuankai Li, Yixin Ye, and Dequan Wang · 2025
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