BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language Paper • 2606.22138 • Published 5 days ago • 20
Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding Paper • 2605.02290 • Published May 4 • 42
AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs Paper • 2605.15565 • Published May 15 • 17
The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence Paper • 2605.26494 • Published 30 days ago • 41
Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning Paper • 2606.15007 • Published 13 days ago • 15
VibeThinker-3B: Exploring the Frontier of Verifiable Reasoning in Small Language Models Paper • 2606.16140 • Published 10 days ago • 113
Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale Paper • 2606.15079 • Published 12 days ago • 80
Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning Paper • 2605.30039 • Published 27 days ago • 20
MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection Paper • 2605.30288 • Published 27 days ago • 23
STRIDE: Training Data Attribution via Sparse Recovery from Subset Perturbations Paper • 2606.05165 • Published 22 days ago • 4
LLM Explainability with Counterfactual Chains and Causal Graphs Paper • 2606.05972 • Published 21 days ago • 18
PaperFlow: Profiling, Recommending, and Adapting Across Daily Paper Streams Paper • 2606.07454 • Published 20 days ago • 14
Flow-DPPO: Divergence Proximal Policy Optimization for Flow Matching Models Paper • 2606.11025 • Published 16 days ago • 41
MaxProof: Scaling Mathematical Proof with Generative-Verifier RL and Population-Level Test-Time Scaling Paper • 2606.13473 • Published 14 days ago • 90
Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs Paper • 2604.10480 • Published Apr 12 • 20
Nemotron-Post-Training-v3 Collection Collection of datasets used in the post-training phase of Nemotron Nano, Super, and Ultra v3. • 50 items • Updated 13 days ago • 167
Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration? Paper • 2603.03202 • Published Mar 3 • 18
CoDiQ: Test-Time Scaling for Controllable Difficult Question Generation Paper • 2602.01660 • Published Feb 2 • 8
Closing the Data Loop: Using OpenDataArena to Engineer Superior Training Datasets Paper • 2601.09733 • Published Dec 30, 2025 • 9