SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs Paper • 2512.04746 • Published 4 days ago • 11
SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs Paper • 2512.04746 • Published 4 days ago • 11
view post Post 2728 🚀 SignRoundV2 for LLM quantization: PTQ-level cost, QAT-level accuracy — yes, even at 2 bits. SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs (2512.04746) See translation 🔥 3 3 + Reply
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence Paper • 2511.18538 • Published 15 days ago • 244
Stabilizing Reinforcement Learning with LLMs: Formulation and Practices Paper • 2512.01374 • Published 7 days ago • 79
Stabilizing Reinforcement Learning with LLMs: Formulation and Practices Paper • 2512.01374 • Published 7 days ago • 79