| # | Title | Link |
|---|
| 1 | DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning | 2501.12948.html |
| 2 | MangaNinja: Line Art Colorization with Precise Reference Following | 2501.08332.html |
| 3 | MiniMax-01: Scaling Foundation Models with Lightning Attention | 2501.08313.html |
| 4 | TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks | 2412.14161.html |
| 5 | Long Context vs. RAG for LLMs: An Evaluation and Revisits | 2501.01880.html |
| 6 | rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking | 2501.04519.html |
| 7 | DeepSeek-V3 Technical Report | 2412.19437.html |
| 8 | Qwen2.5 Technical Report | 2412.15115.html |
| 9 | A Survey on Large Language Model based Autonomous Agents | 2308.11432.html |
| 10 | Evaluating and Aligning CodeLLMs on Human Preference | 2412.05210.html |
| 11 | Shiksha: A Technical Domain focused Translation Dataset and Model for Indian Languages | 2412.09025.html |
| 12 | AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials | 2412.09605.html |
| 13 | Phi-4 Technical Report | 2412.08905.html |