Key papers

• Influence Guided Sampling for Domain Adaptation of Text Retrievers (2026)
  Meet Doshi et al.
  1.94
• Free Lunch for Pass@k? Low Cost Diverse Sampling for Diffusion Language Models (2026)
  Sean Lamont et al.
  1.94
• Temporal Gains, Spatial Costs: Revisiting Video Fine-Tuning in Multimodal Large Language Models (2026)
  Linghao Zhang et al.
  1.94
• Model Capability Dominates: Inference-Time Optimization Lessons from AIMO 3 (2026)
  Natapong Nitarach
  1.94
• N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization (2026)
  Xukun Zhu et al.
  1.94
• GD^2PO: Mitigating Multi-Reward Conflicts via Group-Dynamic reward-Decoupled Policy Optimization (2026)
  Haotian Liu et al.
  1.94
• Manifold Bandits: Bayesian Curriculum Learning over the Latent Geometry of Large Language Models (2026)
  Darrien McKenzie et al.
  1.94
• EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL (2026)
  Minrui Xu et al.
  1.89
• Signals: Trajectory Sampling and Triage for Agentic Interactions (2026)
  Shuguang Chen et al.
  1.83
• Small Vision-Language Models are Smart Compressors for Long Video Understanding (2026)
  Junjie Fei et al.
  1.83
• TIP: Token Importance in On-Policy Distillation (2026)
  Yuanda Xu et al.
  1.83
• Reinforcement Learning via Value Gradient Flow (2026)
  Haoran Xu et al.
  1.83
• LeapAlign: Post-Training Flow Matching Models at Any Generation Step by Building Two-Step Trajectories (2026)
  Zhanhao Liang et al.
  1.83
• CurveStream: Boosting Streaming Video Understanding in MLLMs via Curvature-Aware Hierarchical Visual Memory Management (2026)
  Chao Wang et al.
  1.78
• Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations (2026)
  Wei Liu et al.
  1.72
• Online Causal Kalman Filtering for Stable and Effective Policy Optimization (2026)
  Shuo He et al.
  1.72
• Statistical Estimation of Adversarial Risk in Large Language Models under Best-of-N Sampling (2026)
  Mingqian Feng et al.
  1.67
• Chain-of-Retrieval Augmented Generation (2025)
  Liang Wang et al.
  1.28
• ACECODER: Acing Coder RL via Automated Test-Case Synthesis (2025)
  Huaye Zeng et al.
  1.28
• Region-Adaptive Sampling for Diffusion Transformers (2025)
  Ziming Liu et al.
  1.28
• Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation (2025)
  Sucheng Ren et al.
  1.28
• Learning Few-Step Diffusion Models by Trajectory Distribution Matching (2025)
  Yihong Luo et al.
  1.28
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale (2025)
  Qiying Yu et al.
  1.28
• Bridging Supervised Learning and Reinforcement Learning in Math Reasoning (2025)
  Huayu Chen et al.
  1.28
• Normalized Attention Guidance: Universal Negative Guidance for Diffusion Model (2025)
  Dar-Yen Chen et al.
  1.28
• Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation (2025)
  Shufan Li et al.
  1.28
• Toward Effective Tool-Integrated Reasoning via Self-Evolved Preference Learning (2025)
  Yifei Chen et al.
  1.28
• FrameThinker: Learning to Think with Long Videos via Multi-Turn Frame Spotlighting (2025)
  Zefeng He et al.
  1.28
• Graph2Eval: Automatic Multimodal Task Generation for Agents via Knowledge Graphs (2025)
  Yurun Chen et al.
  1.28
• VR-Thinker: Boosting Video Reward Models through Thinking-with-Image Reasoning (2025)
  Qunzhong Wang et al.
  1.28
• Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation (2025)
  Enshu Liu et al.
  1.28
• The Best of N Worlds: Aligning Reinforcement Learning with Best-of-N Sampling via max@k Optimisation (2025)
  Farid Bagirov et al.
  1.28
• Flow Map Distillation Without Data (2025)
  Shangyuan Tong et al.
  1.28
• Image-Free Timestep Distillation via Continuous-Time Consistency with Trajectory-Sampled Pairs (2025)
  Bao Tang et al.
  1.28
• Beyond Token-level Supervision: Unlocking the Potential of Decoding-based Regression via Reinforcement Learning (2025)
  Ming Chen et al.
  1.28
• Learning Unmasking Policies for Diffusion Language Models (2025)
  Metod Jazbec et al.
  1.28
• On Architectural Compression of Text-to-Image Diffusion Models (2023)
  Bo-Kyeong Kim et al.
  —
• ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation (2023)
  Zhengyi Wang et al.
  —
• A Static Evaluation of Code Completion by Large Language Models (2023)
  Hantian Ding et al.
  —
• Supervised Pretraining Can Learn In-Context Reinforcement Learning (2023)
  Jonathan N. Lee et al.
  —
• Scaling Relationship on Learning Mathematical Reasoning with Large Language Models (2023)
  Zheng Yuan et al.
  —
• PALP: Prompt Aligned Personalization of Text-to-Image Models (2024)
  Moab Arar et al.
  —
• CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay (2024)
  Natasha Butt et al.
  —
• Trajectory Consistency Distillation (2024)
  Jianbin Zheng et al.
  —
• RL for Consistency Models: Faster Reward Guided Text-to-Image Generation (2024)
  Owen Oertell et al.
  —
• Improved Distribution Matching Distillation for Fast Image Synthesis (2024)
  Tianwei Yin et al.
  —
• Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models (2024)
  Guanting Dong et al.
  —
• VLRewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models (2024)
  Lei Li et al.
  —