4 papers
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-AI, Anyi Xu, Bangcai Lin +315
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…
CASTLE: Contrastive and Seed-Guided Training for Cold-Start Natural Language Search
Wendy Ran Wei, Hao Li, Weiwei Guo +9
Deploying natural language search systems presents a critical cold-start challenge: no real user queries to learn linguistic patterns, and no relevance labels to train ranking mode…
DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels
Haolei Bai, Lingcheng Kong, Xueyi Chen +3
Diffusion large language models (dLLMs) have emerged as a compelling alternative to autoregressive (AR) LLMs, owing to their capacity for parallel token generation. This paradigm i…
Training Hybrid Quantum Policies with Classical Surrogates for Actor-Critic Reinforcement Learning
Jie Luo, Jeremy Kulcsar, Xueyin Chen +2
Reading out a parametrized quantum circuit through finite-shot measurements introduces a discrete stochastic component into hybrid quantum-classical neural networks, making gradien…