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Found 6 papers, 4 papers with code
FP8-LM: Training FP8 Large Language Models
In this paper, we explore FP8 low-bit data formats for efficient training of large language models (LLMs).
Knowledge Transfer-Driven Few-Shot Class-Incremental Learning
Concretely, RESA mimics the real incremental setting and constructs pseudo incremental tasks globally and locally, where the global pseudo incremental tasks are designed to coincide with the learning objective of FSCIL and the local pseudo incremental tasks are designed to improve the model's plasticity, respectively.
Logic Diffusion for Knowledge Graph Reasoning
Most recent works focus on answering first order logical queries to explore the knowledge graph reasoning via multi-hop logic predictions.
A Neural Corpus Indexer for Document Retrieval
To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query.
Multi-Sample based Contrastive Loss for Top-k Recommendation
Therefore, we propose a Multi-Sample based Contrastive Loss (MSCL) function which solves the two problems by balancing the importance of positive and negative samples and data augmentation.
GraphSeq2Seq: Graph-Sequence-to-Sequence for Neural Machine Translation
In this paper, we propose a Graph-Sequence-to-Sequence(GraphSeq2Seq) model to fuse the dependency graph among words into the traditional Seq2Seq framework.
