Key papers

• s1: Simple test-time scaling (2025)
  Niklas Muennighoff et al.
  9.77
• BlenderGym: Benchmarking Foundational Model Systems for Graphics Editing (2025)
  Yunqi Gu et al.
  2.87
• Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification (2026)
  Yuxuan Wan et al.
  1.94
• CoDiQ: Test-Time Scaling for Controllable Difficult Question Generation (2026)
  Zhongyuan Peng et al.
  1.94
• A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces (2026)
  Mingxuan Du et al.
  1.94
• Fine-T2I: An Open, Large-Scale, and Diverse Dataset for High-Quality T2I Fine-Tuning (2026)
  Xu Ma et al.
  1.94
• RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment (2026)
  Liyao Jiang et al.
  1.94
• Believe Your Model: Distribution-Guided Confidence Calibration (2026)
  Xizhong Yang et al.
  1.94
• Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders (2026)
  Boqiang Zhang et al.
  1.94
• PLDR-LLMs Reason At Self-Organized Criticality (2026)
  Burc Gokden
  1.94
• AIBench: Evaluating Visual-Logical Consistency in Academic Illustration Generation (2026)
  Zhaohe Liao et al.
  1.94
• DR-Venus: Towards Frontier Edge-Scale Deep Research Agents with Only 10K Open Data (2026)
  Venus Team et al.
  1.94
• Building a Precise Video Language with Human-AI Oversight (2026)
  Zhiqiu Lin et al.
  1.94
• Improving Vision-language Models with Perception-centric Process Reward Models (2026)
  Yingqian Min et al.
  1.94
• Continuous Latent Diffusion Language Model (2026)
  Hongcan Guo et al.
  1.94
• DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices (2026)
  Chenyang Song et al.
  1.94
• LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws (2026)
  Xu Ouyang et al.
  1.94
• Why Larger Models Learn More: Effects of Capacity, Interference, and Rare-Task Retention (2026)
  Jing Huang et al.
  1.94
• SDR: Set-Distance Rewards for Radiology Report Generation (2026)
  Halil Ibrahim Gulluk et al.
  1.94
• APPO: Agentic Procedural Policy Optimization (2026)
  Xucong Wang et al.
  1.94
• Trust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding (2026)
  Jingyuan Huang et al.
  1.94
• HumanScale: Egocentric Human Video Can Outperform Real-Robot Data for Embodied Pretraining (2026)
  Juncheng Ma et al.
  1.94
• DataComp-VLM: Improved Open Datasets for Vision-Language Models (2026)
  Matteo Farina et al.
  1.94
• TESSERA v2: Scaling Pixel-wise Earth Foundation Models (2026)
  Zhengpeng Feng et al.
  1.94
• UniMixer: A Unified Architecture for Scaling Laws in Recommendation Systems (2026)
  Mingming Ha et al.
  1.83
• Reinforcement Learning via Value Gradient Flow (2026)
  Haoran Xu et al.
  1.83
• DynaMoE: Dynamic Token-Level Expert Activation with Layer-Wise Adaptive Capacity for Mixture-of-Experts Neural Networks (2026)
  Gökdeniz Gülmez
  1.78
• Beyond Language Modeling: An Exploration of Multimodal Pretraining (2026)
  Shengbang Tong et al.
  1.78
• Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations (2026)
  Wei Liu et al.
  1.72
• Learning from Trials and Errors: Reflective Test-Time Planning for Embodied LLMs (2026)
  Yining Hong et al.
  1.72
• X-Coder: Advancing Competitive Programming with Fully Synthetic Tasks, Solutions, and Tests (2026)
  Jie Wu et al.
  1.67
• Statistical Estimation of Adversarial Risk in Large Language Models under Best-of-N Sampling (2026)
  Mingqian Feng et al.
  1.67
• Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models (2025)
  Samira Abnar et al.
  1.28
• Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step (2025)
  Ziyu Guo et al.
  1.28
• APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding (2025)
  Xinyu Yang et al.
  1.28
• Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment (2025)
  Chenghao Fan et al.
  1.28
• An Empirical Study on Eliciting and Improving R1-like Reasoning Models (2025)
  Zhipeng Chen et al.
  1.28
• Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo (2025)
  Zachary Charles et al.
  1.28
• VerifiAgent: a Unified Verification Agent in Language Model Reasoning (2025)
  Jiuzhou Han et al.
  1.28
• VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model (2025)
  Haozhan Shen et al.
  1.28
• DataDecide: How to Predict Best Pretraining Data with Small Experiments (2025)
  Ian Magnusson 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
• Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning (2025)
  Yinjie Wang et al.
  1.28
• Kinetics: Rethinking Test-Time Scaling Laws (2025)
  Ranajoy Sadhukhan et al.
  1.28
• Scaling Laws for Optimal Data Mixtures (2025)
  Mustafa Shukor et al.
  1.28
• Inverse Scaling in Test-Time Compute (2025)
  Aryo Pradipta Gema et al.
  1.28
• Efficient Agents: Building Effective Agents While Reducing Cost (2025)
  Ningning Wang et al.
  1.28
• Retrieval-augmented reasoning with lean language models (2025)
  Ryan Sze-Yin Chan et al.
  1.28
• RewardDance: Reward Scaling in Visual Generation (2025)
  Jie Wu et al.
  1.28
• Beyond Outliers: A Study of Optimizers Under Quantization (2025)
  Georgios Vlassis et al.
  1.28
• Hybrid Architectures for Language Models: Systematic Analysis and Design Insights (2025)
  Sangmin Bae et al.
  1.28
• Revisiting Long-context Modeling from Context Denoising Perspective (2025)
  Zecheng Tang et al.
  1.28
• Parallel Test-Time Scaling for Latent Reasoning Models (2025)
  Runyang You et al.
  1.28
• EAGER: Entropy-Aware GEneRation for Adaptive Inference-Time Scaling (2025)
  Daniel Scalena et al.
  1.28
• Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations (2025)
  Jinkun Chen et al.
  1.28
• Scaling Laws for Deepfake Detection (2025)
  Wenhao Wang et al.
  1.28
• ATLAS: Adaptive Transfer Scaling Laws for Multilingual Pretraining, Finetuning, and Decoding the Curse of Multilinguality (2025)
  Shayne Longpre et al.
  1.28
• The Sequential Edge: Inverse-Entropy Voting Beats Parallel Self-Consistency at Matched Compute (2025)
  Aman Sharma et al.
  1.28
• RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments (2025)
  Zhiyuan Zeng et al.
  1.28
• Generalist Foundation Models Are Not Clinical Enough for Hospital Operations (2025)
  Lavender Y. Jiang et al.
  1.28