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Found 5 papers, 1 papers with code
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM
Recent advancements in code large language models (LLMs) have demonstrated remarkable capabilities in code generation and understanding.
Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs
Ultimately, our experimental findings demonstrate that a 300B MoE LLM can be effectively trained on lower-performance devices while achieving comparable performance to models of a similar scale, including dense and MoE models.
Context-Aware Lifelong Sequential Modeling for Online Click-Through Rate Prediction
Central to this process is the attention mechanism, which extracts interest representations with respect to candidate items from the user sequence.
Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation
The idea is to supplement the GNN-based main supervised recommendation task with the temporal representation via an auxiliary cross-view contrastive learning mechanism.
Infinite Hidden Semi-Markov Modulated Interaction Point Process
The proposed approach can simultaneously model both the observations and arrival times of temporal events, and determine the number of latent states from data.
