Key papers

• An Empirical Study on Preference Tuning Generalization and Diversity Under Domain Shift (2026)
  Constantinos Karouzos 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
• Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning (2026)
  NVIDIA et al.
  1.94
• Multimodal Representation Alignment for Image Generation: Text-Image Interleaved Control Is Easier Than You Think (2025)
  Liang Chen et al.
  1.28
• In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer (2025)
  Zechuan Zhang et al.
  1.28
• YoChameleon: Personalized Vision and Language Generation (2025)
  Thao Nguyen et al.
  1.28
• MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning (2025)
  Run-Ze Fan et al.
  1.28
• Cut2Next: Generating Next Shot via In-Context Tuning (2025)
  Jingwen He et al.
  1.28
• Fantastic Pretraining Optimizers and Where to Find Them (2025)
  Kaiyue Wen et al.
  1.28
• Visual Representation Alignment for Multimodal Large Language Models (2025)
  Heeji Yoon et al.
  1.28
• Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs (2025)
  Richard Cornelius Suwandi et al.
  1.28
• AdvChain: Adversarial Chain-of-Thought Tuning for Robust Safety Alignment of Large Reasoning Models (2025)
  Zihao Zhu et al.
  1.28
• Understanding and Harnessing Sparsity in Unified Multimodal Models (2025)
  Shwai He et al.
  1.28
• InfiniteVL: Synergizing Linear and Sparse Attention for Highly-Efficient, Unlimited-Input Vision-Language Models (2025)
  Hongyuan Tao et al.
  1.28
• OctoPack: Instruction Tuning Code Large Language Models (2023)
  Niklas Muennighoff et al.
  —
• VL-GPT: A Generative Pre-trained Transformer for Vision and Language Understanding and Generation (2023)
  Jinguo Zhu et al.
  —
• WaveCoder: Widespread And Versatile Enhanced Instruction Tuning with Refined Data Generation (2023)
  Zhaojian Yu et al.
  —
• Generative Representational Instruction Tuning (2024)
  Niklas Muennighoff et al.
  —
• DeepSeek-VL: Towards Real-World Vision-Language Understanding (2024)
  Haoyu Lu et al.
  —
• PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM (2024)
  Tao Yang et al.
  —
• MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs (2024)
  Ziyu Liu et al.
  —
• JEN-1 DreamStyler: Customized Musical Concept Learning via Pivotal Parameters Tuning (2024)
  Boyu Chen et al.
  —
• ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities (2024)
  Peng Xu et al.
  —
• VITA: Towards Open-Source Interactive Omni Multimodal LLM (2024)
  Chaoyou Fu et al.
  —
• In-Context LoRA for Diffusion Transformers (2024)
  Lianghua Huang et al.
  —
• M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework (2024)
  Yew Ken Chia et al.
  —
• VLsI: Verbalized Layers-to-Interactions from Large to Small Vision Language Models (2024)
  Byung-Kwan Lee et al.
  —
• GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-training (2024)
  Renqiu Xia et al.
  —
• TOMG-Bench: Evaluating LLMs on Text-based Open Molecule Generation (2024)
  Jiatong Li et al.
  —