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Found 11 papers, 3 papers with code
EASRec: Elastic Architecture Search for Efficient Long-term Sequential Recommender Systems
Our research addresses the computational and resource inefficiencies that current Sequential Recommender Systems (SRSs) suffer from.
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts
However, the gate's routing mechanism also gives rise to narrow vision: the individual MoE's expert fails to use more samples in learning the allocated sub-task, which in turn limits the MoE to further improve its generalization ability.
CharPoet: A Chinese Classical Poetry Generation System Based on Token-free LLM
A video demonstration of CharPoet is available at https://youtu. be/voZ25qEp3Dc.
Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy
Hence, this paper presents a generic framework for accelerating the inference process, resulting in a substantial increase in speed and cost reduction for our RAG system, with lossless generation accuracy.
GreenFlow: A Computation Allocation Framework for Building Environmentally Sound Recommendation System
of a cascade RS, when a user triggers a request, we define two actions that determine the computation: (1) the trained instances of models with different computational complexity; and (2) the number of items to be inferred in the stage.
Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup
In our research, we constructed a dataset, the Multimodal Advertisement Audition Dataset (MAAD), from real-world scenarios within Alipay, and conducted experiments to validate the reliability of our proposed strategy.
Intelligent Virtual Assistants with LLM-based Process Automation
This paper proposes a novel LLM-based virtual assistant that can automatically perform multi-step operations within mobile apps based on high-level user requests.
Fast Chain-of-Thought: A Glance of Future from Parallel Decoding Leads to Answers Faster
In this work, we propose FastCoT, a model-agnostic framework based on parallel decoding without any further training of an auxiliary model or modification to the LLM itself.
StylePrompter: All Styles Need Is Attention
We then prove that StylePrompter lies in a more disentangled $\mathcal{W^+}$ and show the controllability of SMART.
Tensorized Hypergraph Neural Networks
THNN is a faithful hypergraph modeling framework through high-order outer product feature message passing and is a natural tensor extension of the adjacency-matrix-based graph neural networks.
hpGAT: High-order Proximity Informed Graph Attention Network
Graph neural networks (GNNs) have recently made remarkable breakthroughs in the paradigm of learning with graph-structured data.
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