{"list":"other","total":51,"rows":[{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"2304.08485","title":"Visual Instruction Tuning","created":"2023-04-17","cited_by_count":7869},{"id":"1612.00796","title":"Overcoming catastrophic forgetting in neural networks","created":"2016-12-02","cited_by_count":4787},{"id":"2310.03744","title":"Improved Baselines with Visual Instruction Tuning","created":"2023-10-05","cited_by_count":4418},{"id":"2312.14238","title":"InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks","created":"2023-12-21","cited_by_count":2565},{"id":"1612.00837","title":"Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering","created":"2016-12-02","cited_by_count":2516},{"id":"1606.09282","title":"Learning without Forgetting","created":"2016-06-29","cited_by_count":2496},{"id":"2107.13586","title":"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","created":"2021-07-28","cited_by_count":2234},{"id":"2307.06281","title":"MMBench: Is Your Multi-modal Model an All-around Player?","created":"2023-07-12","cited_by_count":2141},{"id":"2006.16241","title":"The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization","created":"2020-06-29","cited_by_count":1850},{"id":"2305.10355","title":"Evaluating Object Hallucination in Large Vision-Language Models","created":"2023-05-17","cited_by_count":1729},{"id":"2306.13394","title":"MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models","created":"2023-06-23","cited_by_count":1652},{"id":"1505.04870","title":"Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models","created":"2015-05-19","cited_by_count":1362},{"id":"2307.16125","title":"SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension","created":"2023-07-30","cited_by_count":940},{"id":"2306.13549","title":"A Survey on Multimodal Large Language Models","created":"2023-06-23","cited_by_count":909},{"id":"2302.00487","title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application","created":"2023-01-31","cited_by_count":872},{"id":"1802.08218","title":"VizWiz Grand Challenge: Answering Visual Questions from Blind People","created":"2018-02-22","cited_by_count":858},{"id":"1603.07396","title":"A Diagram Is Worth A Dozen Images","created":"2016-03-24","cited_by_count":804},{"id":"2312.14150","title":"DriveLM: Driving with Graph Visual Question Answering","created":"2023-12-21","cited_by_count":536},{"id":"2003.10286","title":"PathVQA: 30000+ Questions for Medical Visual Question Answering","created":"2020-03-07","cited_by_count":475},{"id":"2010.15277","title":"Class-incremental learning: survey and performance evaluation on image classification","created":"2020-10-28","cited_by_count":449},{"id":"2310.14152","title":"Orthogonal Subspace Learning for Language Model Continual Learning","created":"2023-10-22","cited_by_count":312},{"id":"2110.13214","title":"IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning","created":"2021-10-25","cited_by_count":267},{"id":"2302.03648","title":"Class-Incremental Learning: A Survey","created":"2023-02-07","cited_by_count":209},{"id":"2003.07333","title":"RSVQA: Visual Question Answering for Remote Sensing Data","created":"2020-03-16","cited_by_count":203},{"id":"2403.00231","title":"Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models","created":"2024-03-01","cited_by_count":139},{"id":"2208.05358","title":"CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning","created":"2022-08-10","cited_by_count":120},{"id":"2211.08545","title":"MapQA: A Dataset for Question Answering on Choropleth Maps","created":"2022-11-15","cited_by_count":85},{"id":"2112.12533","title":"PyCIL: A Python Toolbox for Class-Incremental Learning","created":"2021-12-23","cited_by_count":83},{"id":"2411.15296","title":"MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs","created":"2024-11-22","cited_by_count":72},{"id":"2309.07117","title":"PILOT: A Pre-Trained Model-Based Continual Learning Toolbox","created":"2023-09-13","cited_by_count":64},{"id":"2403.08350","title":"CoIN: A Benchmark of Continual Instruction tuNing for Multimodel Large Language Model","created":"2024-03-13","cited_by_count":61},{"id":"2410.05352","title":"Recent Advances of Multimodal Continual Learning: A Comprehensive Survey","created":"2024-10-07","cited_by_count":39},{"id":"2503.00413","title":"CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering","created":"2025-03-01","cited_by_count":37},{"id":"2208.12037","title":"Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task","created":"2022-08-24","cited_by_count":35},{"id":"2302.01766","title":"Avalanche: A PyTorch Library for Deep Continual Learning","created":"2023-02-02","cited_by_count":33},{"id":"2505.02486","title":"SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning","created":"2025-05-05","cited_by_count":33},{"id":"2503.12941","title":"HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model","created":"2025-03-17","cited_by_count":31},{"id":"2410.05849","title":"ModalPrompt: Towards Efficient Multimodal Continual Instruction Tuning with Dual-Modality Guided Prompt","created":"2024-10-08","cited_by_count":30},{"id":"2306.12646","title":"Learnability and Algorithm for Continual Learning","created":"2023-06-22","cited_by_count":28},{"id":"2308.01430","title":"FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis","created":"2023-07-31","cited_by_count":28},{"id":"2205.15445","title":"Continual Object Detection: A review of definitions, strategies, and challenges","created":"2022-05-30","cited_by_count":25},{"id":"2506.05453","title":"MLLM-CL: Continual Learning for Multimodal Large Language Models","created":"2025-06-05","cited_by_count":23},{"id":"2503.10627","title":"SciVerse: Unveiling the Knowledge Comprehension and Visual Reasoning of LMMs on Multi-modal Scientific Problems","created":"2025-03-13","cited_by_count":22},{"id":"2310.14277","title":"A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application","created":"2023-10-22","cited_by_count":21},{"id":"2506.08666","title":"LLaVA-c: Continual Improved Visual Instruction Tuning","created":"2025-06-10","cited_by_count":14},{"id":"2312.07887","title":"Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models","created":"2023-12-13","cited_by_count":13},{"id":"2503.12897","title":"Federated Continual Instruction Tuning","created":"2025-03-17","cited_by_count":12},{"id":"2506.13045","title":"Continual Learning for Generative AI: From LLMs to MLLMs and Beyond","created":"2025-06-16","cited_by_count":12},{"id":"2503.01887","title":"When Continue Learning Meets Multimodal Large Language Model: A Survey","created":"2025-02-27","cited_by_count":9},{"id":"2407.14029","title":"PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental Learning","created":"2024-07-19","cited_by_count":8}],"next_cursor":null}