BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models
This paper falls in the category of parameter efficient fine-tuning, where the goal is to use as few parameters as possible to achieve almost the same accuracy as if we were to fine-tune the whole model.
Review - Pretraining Representations for Data-Efficient Reinforcement LearningAssemblyai
Review - ALBERT: A Lite BERT for Self-supervised Learning of Language RepresentationsAssemblyai
Review - data2vec: A General Framework for Self-supervised Learning in Speech, Vision, and LanguageAssemblyai
Review - SimCLS and RefSum - Summarization TechniquesAssemblyai
Redact PII in Audio with Make and AssemblyAIAssemblyai
Review - VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised LearningAssemblyai
10 best AI observability tools for monitoring and evaluating agents in 2026Mintlify
Trained on 100,000+ Voices: Deepgram Unveils Next-Gen Speaker Diarization and Language DetectionDeepgram
The Language of LGBTQ Inclusion and Allyship - Deepgram Blog ⚡️Deepgram
New Spanish and Turkish Language Models and Updated General Models - Deepgram Blog ⚡️Deepgram
AI frameworks: Definition, types, and how to chooseZapier
How CoverDoc uses AI to revolutionize cover letter writingZapier
How Argo CD and OpenShift Enable GitOps for DevelopersThenewstack
OData or GraphQL? The Best Tech for Developing an API Is Neither or Both!Thenewstack
Oso Unbundles Security AuthorizationThenewstack
Discovered Stacks: One Place for All Your InfrastructurePulumi
IaC Best Practices: Implementing RBAC and SecurityPulumi
Pkg.go.dev has a new look! - The Go Programming LanguageGo
Inside the Go Playground - The Go Programming LanguageGo
Real Go Projects: SmartTwitter and web.go - The Go Programming LanguageGo
