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Found 4 papers, 2 papers with code
Sparse Matrix in Large Language Model Fine-tuning
In this work, we introduce a method for selecting sparse sub-matrices that aim to minimize the performance gap between PEFT vs. full fine-tuning (FT) while also reducing both fine-tuning computational cost and memory cost.
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
The ML community is rapidly exploring techniques for prompting language models (LMs) and for stacking them into pipelines that solve complex tasks.
Composing and Decomposing Op-Based CRDTs with Semidirect Products
Although it reproduces common CRDT semantics, the semidirect product can be viewed as a restricted kind of operational transformation, thus forming a bridge between these two opposing techniques for constructing replicated data types.
Distributed, Parallel, and Cluster Computing
Partisan: Enabling Cloud-Scale Erlang Applications
Partisan is a topology-agnostic distributed programming model and distribution layer that supports several network topologies for different application scenarios: full mesh, peer-to-peer, client-server, and publish-subscribe.
Distributed, Parallel, and Cluster Computing
