Key papers

• UniX: Unifying Autoregression and Diffusion for Chest X-Ray Understanding and Generation (2026)
  Ruiheng Zhang et al.
  1.94
• OmegaUse: Building a General-Purpose GUI Agent for Autonomous Task Execution (2026)
  Le Zhang et al.
  1.94
• Qwen3-ASR Technical Report (2026)
  Xian Shi et al.
  1.94
• Rethinking Generative Recommender Tokenizer: Recsys-Native Encoding and Semantic Quantization Beyond LLMs (2026)
  Yu Liang et al.
  1.94
• Data Darwinism Part I: Unlocking the Value of Scientific Data for Pre-training (2026)
  Yiwei Qin et al.
  1.94
• VAREX: A Benchmark for Multi-Modal Structured Extraction from Documents (2026)
  Udi Barzelay et al.
  1.94
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies (2026)
  Xuning Yang et al.
  1.94
• LongAttnComp: Cross-Family Context Compression for Long-Context Reasoning (2026)
  Mengmeng Ji et al.
  1.94
• HumanScale: Egocentric Human Video Can Outperform Real-Robot Data for Embodied Pretraining (2026)
  Juncheng Ma et al.
  1.94
• TESSERA v2: Scaling Pixel-wise Earth Foundation Models (2026)
  Zhengpeng Feng et al.
  1.94
• Dynin-Omni: Omnimodal Unified Large Diffusion Language Model (2026)
  Jaeik Kim et al.
  1.83
• Heterogeneous Scientific Foundation Model Collaboration (2026)
  Zihao Li et al.
  1.83
• Thinking While Speaking: Inference-Time Knowledge Transfer for Responsive and Intelligent Conversational Voice Agents (2026)
  Vidya Srinivas et al.
  1.56
• ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from Transformer (2025)
  Lin Yueyu et al.
  1.28
• NatureLM: Deciphering the Language of Nature for Scientific Discovery (2025)
  Yingce Xia et al.
  1.28
• SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency Distillation (2025)
  Junsong Chen et al.
  1.28
• FullDiT: Multi-Task Video Generative Foundation Model with Full Attention (2025)
  Xuan Ju et al.
  1.28
• Seed1.5-VL Technical Report (2025)
  Dong Guo et al.
  1.28
• Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents (2025)
  Jenny Zhang et al.
  1.28
• Visual Representation Alignment for Multimodal Large Language Models (2025)
  Heeji Yoon et al.
  1.28
• Scaling Agents via Continual Pre-training (2025)
  Liangcai Su et al.
  1.28
• SAIL-VL2 Technical Report (2025)
  Weijie Yin et al.
  1.28
• Video models are zero-shot learners and reasoners (2025)
  Thaddäus Wiedemer et al.
  1.28
• AlphaApollo: Orchestrating Foundation Models and Professional Tools into a Self-Evolving System for Deep Agentic Reasoning (2025)
  Zhanke Zhou et al.
  1.28
• AIonopedia: an LLM agent orchestrating multimodal learning for ionic liquid discovery (2025)
  Yuqi Yin et al.
  1.28
• Generalist Foundation Models Are Not Clinical Enough for Hospital Operations (2025)
  Lavender Y. Jiang et al.
  1.28
• LongCat-Image Technical Report (2025)
  Meituan LongCat Team 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.
  —
• Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models (2023)
  Haoning Wu et al.
  —
• InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks (2023)
  Zhe Chen et al.
  —
• AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents (2024)
  Michael Ahn et al.
  —
• SymbolicAI: A framework for logic-based approaches combining generative models and solvers (2024)
  Marius-Constantin Dinu et al.
  —
• Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use (2024)
  Imad Eddine Toubal et al.
  —
• SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation (2024)
  Yuying Ge et al.
  —
• HEMM: Holistic Evaluation of Multimodal Foundation Models (2024)
  Paul Pu Liang et al.
  —
• MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models (2024)
  Mahir Labib Dihan et al.
  —