Key papers

• NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors (2026)
  Lingfeng Ren et al.
  1.94
• Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders (2026)
  Boqiang Zhang et al.
  1.94
• HiMu: Hierarchical Multimodal Frame Selection for Long Video Question Answering (2026)
  Dan Ben-Ami et al.
  1.94
• Do VLMs Need Vision Transformers? Evaluating State Space Models as Vision Encoders (2026)
  Shang-Jui Ray Kuo et al.
  1.94
• Image Generators are Generalist Vision Learners (2026)
  Valentin Gabeur et al.
  1.94
• Delta-Adapter: Scalable Exemplar-Based Image Editing with Single-Pair Supervision (2026)
  Jiacheng Chen et al.
  1.94
• Beyond Scalar Distances: Semantic Attribute Gradients from Frozen MLLMs for Visual Embeddings (2026)
  Shubhang Bhatnagar et al.
  1.94
• Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models (2026)
  Yu Zeng et al.
  1.72
• DUET-VLM: Dual stage Unified Efficient Token reduction for VLM Training and Inference (2026)
  Aditya Kumar Singh et al.
  1.72
• AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation (2025)
  Junjie He et al.
  1.28
• Introducing Visual Perception Token into Multimodal Large Language Model (2025)
  Runpeng Yu et al.
  1.28
• Taking Notes Brings Focus? Towards Multi-Turn Multimodal Dialogue Learning (2025)
  Jiazheng Liu et al.
  1.28
• Should VLMs be Pre-trained with Image Data? (2025)
  Sedrick Keh et al.
  1.28
• Instruction-Guided Autoregressive Neural Network Parameter Generation (2025)
  Soro Bedionita et al.
  1.28
• Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding (2025)
  Tao Zhang et al.
  1.28
• Unified Multimodal Chain-of-Thought Reward Model through Reinforcement Fine-Tuning (2025)
  Yibin Wang et al.
  1.28
• Seed1.5-VL Technical Report (2025)
  Dong Guo et al.
  1.28
• OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning (2025)
  Zhaochen Su et al.
  1.28
• Thinking with Generated Images (2025)
  Ethan Chern et al.
  1.28
• Vision Language Models are Biased (2025)
  An Vo et al.
  1.28
• Vision-Language-Vision Auto-Encoder: Scalable Knowledge Distillation from Diffusion Models (2025)
  Tiezheng Zhang et al.
  1.28
• Scaling Laws for Optimal Data Mixtures (2025)
  Mustafa Shukor et al.
  1.28
• Ovis2.5 Technical Report (2025)
  Shiyin Lu et al.
  1.28
• ViExam: Are Vision Language Models Better than Humans on Vietnamese Multimodal Exam Questions? (2025)
  Vy Tuong Dang et al.
  1.28
• Visual Representation Alignment for Multimodal Large Language Models (2025)
  Heeji Yoon et al.
  1.28
• SAIL-VL2 Technical Report (2025)
  Weijie Yin et al.
  1.28
• The Photographer Eye: Teaching Multimodal Large Language Models to See and Critique like Photographers (2025)
  Daiqing Qi et al.
  1.28
• Video models are zero-shot learners and reasoners (2025)
  Thaddäus Wiedemer et al.
  1.28
• GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts (2025)
  Fan Yuan et al.
  1.28
• Multimodal Web Navigation with Instruction-Finetuned Foundation Models (2023)
  Hiroki Furuta et al.
  —
• SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding (2023)
  Haoxiang Wang et al.
  —
• LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents (2023)
  Shilong Liu et al.
  —
• Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization (2023)
  Weiyang Liu et al.
  —
• Weight subcloning: direct initialization of transformers using larger pretrained ones (2023)
  Mohammad Samragh et al.
  —
• InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks (2023)
  Zhe Chen et al.
  —
• Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model (2024)
  Lianghui Zhu et al.
  —
• ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling (2024)
  Siming Yan et al.
  —
• TinyLLaVA: A Framework of Small-scale Large Multimodal Models (2024)
  Baichuan Zhou et al.
  —
• DeepSeek-VL: Towards Real-World Vision-Language Understanding (2024)
  Haoyu Lu et al.
  —
• VisionGPT-3D: A Generalized Multimodal Agent for Enhanced 3D Vision Understanding (2024)
  Chris Kelly et al.
  —
• LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters (2024)
  Xinyu Zhou et al.
  —
• Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models (2024)
  Yushi Hu et al.
  —
• Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models (2024)
  Hengyi Wang et al.
  —
• VITA: Towards Open-Source Interactive Omni Multimodal LLM (2024)
  Chaoyou Fu et al.
  —
• HiRED: Attention-Guided Token Dropping for Efficient Inference of High-Resolution Vision-Language Models in Resource-Constrained Environments (2024)
  Kazi Hasan Ibn Arif et al.
  —
• Hyper-Connections (2024)
  Defa Zhu et al.
  —
• VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos (2024)
  Shehan Munasinghe et al.
  —