DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale Paper • 2609.22978 • Published 10 days ago • 4
DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale Paper • 2609.22978 • Published 10 days ago • 4
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression Paper • 2609.19969 • Published 12 days ago • 188
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression Paper • 2609.19969 • Published 12 days ago • 188
Atria Dawn: The Dawn of Agentic Superintelligence Paper • 2609.15818 • Published 15 days ago • 429
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence Paper • 2606.19348 • Published Apr 26 • 46
Qwen-UI-Agent Technical Report: Toward Next-Generation Real-World Centric Foundation GUI Agents Paper • 2607.28227 • Published Jul 30 • 158
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning Paper • 2501.12948 • Published Jan 22, 2025 • 463
DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation Paper • 2607.05147 • Published Jul 6 • 51
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence Paper • 2606.19348 • Published Apr 26 • 46
TriAttention: Efficient Long Reasoning with Trigonometric KV Compression Paper • 2604.04921 • Published Apr 6 • 113
AgentVista: Evaluating Multimodal Agents in Ultra-Challenging Realistic Visual Scenarios Paper • 2602.23166 • Published Feb 26 • 46
Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems Paper • 2602.08847 • Published Feb 9 • 30
LOCA-bench: Benchmarking Language Agents Under Controllable and Extreme Context Growth Paper • 2602.07962 • Published Feb 8 • 26
LOCA-bench: Benchmarking Language Agents Under Controllable and Extreme Context Growth Paper • 2602.07962 • Published Feb 8 • 26
view post Post 3641 You can now run Kimi K2.5 locally! 🔥We shrank the 1T model to 240GB (-60%) via Dynamic 1-bit.Get >40 tok/s on 242GB or 622GB VRAM/RAM for near full precision.GGUF: unsloth/Kimi-K2.5-GGUFGuide: https://unsloth.ai/docs/models/kimi-k2.5 See translation 7 replies · 🚀 18 18 😎 4 4 🔥 3 3 👀 2 2 + Reply
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization Paper • 2601.05242 • Published Jan 8 • 235
SWE-RM: Execution-free Feedback For Software Engineering Agents Paper • 2512.21919 • Published Dec 26, 2025 • 10