% Key papers for Open-domain multimodal QA (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages. @inproceedings{icml2016_dynamic_35809, title = {{Dynamic Memory Networks for Visual and Textual Question Answering}}, booktitle = {International Conference on Machine Learning (ICML)}, year = {2016}, url = {https://proceedings.mlr.press/v48/xiong16.html}, } @inproceedings{iclr2017_dynamic_28366, title = {{Dynamic Coattention Networks For Question Answering}}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2017}, url = {https://openreview.net/forum?id=rJeKjwvclx}, } @inproceedings{aaai2018_r3_106011, title = {{R3: Reinforced Ranker-Reader for Open-Domain Question Answering}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2018}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/12053}, } @inproceedings{cvpr2017_are_12065, title = {{Are You Smarter Than a Sixth Grader? Textbook Question Answering for Multimodal Machine Comprehension}}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2017}, } @inproceedings{neurips2022_learn_64503, title = {{Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2022}, url = {https://nips.cc/virtual/2022/poster/54469}, } @inproceedings{aaai2021_dynamic_483, title = {{Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2021}, url = {https://aaai.org/papers/04923-dynamic-neuro-symbolic-knowledge-graph-construction-for-zero-shot-commonsense-question-answering/}, } @inproceedings{icml2023_large_43042, title = {{Large Language Models Struggle to Learn Long-Tail Knowledge}}, booktitle = {International Conference on Machine Learning (ICML)}, year = {2023}, url = {https://icml.cc/virtual/2023/poster/25008}, } @inproceedings{cvpr2019_social_14848, title = {{Social-IQ: A Question Answering Benchmark for Artificial Social Intelligence}}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2019}, } @inproceedings{neurips2018_dialog_57030, title = {{Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2018}, url = {https://nips.cc/virtual/2018/poster/11300}, } @inproceedings{iclr2021_open_30225, title = {{Open Question Answering over Tables and Text}}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2021}, url = {https://iclr.cc/virtual/2021/poster/2617}, } @inproceedings{iclr2019_generative_28815, title = {{Generative Question Answering: Learning to Answer the Whole Question}}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2019}, url = {https://iclr.cc/virtual/2019/poster/1020}, } @inproceedings{iclr2019_coarse_29094, title = {{Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering}}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2019}, url = {https://iclr.cc/virtual/2019/poster/757}, } @inproceedings{aaai2020_getting_103088, title = {{Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2020}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/6398}, } @inproceedings{aaai2017_improving_105976, title = {{Improving Event Causality Recognition with Multiple Background Knowledge Sources Using Multi-Column Convolutional Neural Networks}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2017}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/11005}, } @inproceedings{aaai2019_personalized_99692, title = {{Personalized Question Routing via Heterogeneous Network Embedding}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2019}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/3785}, } @inproceedings{aaai2018_s_105993, title = {{S-Net: From Answer Extraction to Answer Synthesis for Machine Reading Comprehension}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2018}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/12035}, } @inproceedings{aaai2020_manymodalqa_102984, title = {{ManyModalQA: Modality Disambiguation and QA over Diverse Inputs}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2020}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/6294}, } @inproceedings{iclr2023_unikgqa_32758, title = {{UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph}}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2023}, url = {https://iclr.cc/virtual/2023/poster/10823}, } @inproceedings{neurips2018_answerer_56869, title = {{Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2018}, url = {https://nips.cc/virtual/2018/poster/11266}, } @inproceedings{cvpr2018_textbook_13640, title = {{Textbook Question Answering Under Instructor Guidance With Memory Networks}}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2018}, url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Li_Textbook_Question_Answering_CVPR_2018_paper.html}, } @inproceedings{aaai2024_unigen_7696, title = {{UniGen: A Unified Generative Framework for Retrieval and Question Answering with Large Language Models}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2024}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/28714}, } @inproceedings{neurips2024_spiqa_73353, title = {{SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2024}, url = {https://neurips.cc/virtual/2024/poster/97575}, } @inproceedings{aaai2025_audio_8177, title = {{Audio Entailment: Assessing Deductive Reasoning for Audio Understanding}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2025}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/34548}, } @inproceedings{aaai2024_graph_6159, title = {{Graph Reasoning Transformers for Knowledge-Aware Question Answering}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2024}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/29938}, } @inproceedings{iclr2025_benchmarking_82401, title = {{Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent}}, booktitle = {International Conference on Learning Representations (ICLR)}, year = {2025}, url = {https://iclr.cc/virtual/2025/poster/29392}, } @inproceedings{neurips2024_cpapers_71143, title = {{cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2024}, url = {https://neurips.cc/virtual/2024/poster/97802}, } @inproceedings{aaai2025_divide_8785, title = {{Divide-and-Conquer: Tree-structured Strategy with Answer Distribution Estimator for Goal-Oriented Visual Dialogue}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2025}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/32187}, } @inproceedings{aaai2025_retqa_10442, title = {{RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2025}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/34734}, } @inproceedings{icml2026_medmosaic_51640, title = {{MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio}}, booktitle = {International Conference on Machine Learning (ICML)}, year = {2026}, url = {https://openreview.net/forum?id=OMdQJQwp26}, } @inproceedings{icml2026_mmclima_55005, title = {{MMClima: A Framework for Multimodal Climate Science Data and Evaluation}}, booktitle = {International Conference on Machine Learning (ICML)}, year = {2026}, url = {https://openreview.net/forum?id=uiyDqAVhr9}, } @inproceedings{neurips2025_tcm_77929, title = {{TCM-Ladder: A Benchmark for Multimodal Question Answering on Traditional Chinese Medicine}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2025}, url = {https://openreview.net/forum?id=ZDrT1eG54T}, } @inproceedings{cvpr2026_when_98920, title = {{When Robots Should Say ''I Don't Know'': Benchmarking Abstention in Embodied Question Answering}}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2026}, url = {https://openaccess.thecvf.com/content/CVPR2026/html/Wu_When_Robots_Should_Say_I_Dont_Know_Benchmarking_Abstention_in_CVPR_2026_paper.html}, } @inproceedings{aaai2026_domaincqa_108157, title = {{DomainCQA: Crafting Knowledge-Intensive QA from Domain-Specific Charts}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2026}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/40509}, } @inproceedings{icml2025_compositional_47811, title = {{Compositional Condition Question Answering in Tabular Understanding}}, booktitle = {International Conference on Machine Learning (ICML)}, year = {2025}, url = {https://icml.cc/virtual/2025/poster/44789}, } @inproceedings{neurips2026_edma_91915, title = {{EDMA: Entropy-Driven Multimodal Answering}}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2026}, url = {https://neurips.cc/virtual/2026/poster/150520}, } @inproceedings{cvpr2026_chartr_99454, title = {{ChartR: Evaluating Reasoning Accuracy and Robustness in Chart Question Answering}}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2026}, url = {https://openaccess.thecvf.com/content/CVPR2026/html/Chen_ChartR_Evaluating_Reasoning_Accuracy_and_Robustness_in_Chart_Question_Answering_CVPR_2026_paper.html}, } @inproceedings{aaai2026_oida_108921, title = {{OIDA-QA: A Multimodal Benchmark for Analyzing the Opioid Industry Documents Archive}}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, year = {2026}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/41273}, }