Samuel Weinbach
Publications by Year
Research Areas
Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Generative Adversarial Networks and Image Synthesis, Explainable Artificial Intelligence (XAI)
Most-Cited Works
- → GPT-NeoX-20B: An Open-Source Autoregressive Language Model(2022)383 cited
- → Tokenizer Choice For LLM Training: Negligible or Crucial?(2024)23 cited
- → AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation(2023)16 cited
- → M-VADER: A Model for Diffusion with Multimodal Context(2022)7 cited
- → MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation(2023)6 cited
- → MAGMA -- Multimodal Augmentation of Generative Models through Adapter-based Finetuning(2021)5 cited
- → Domain-Level Explainability -- A Challenge for Creating Trust in Superhuman AI Strategies(2020)4 cited
- → T-FREE: Subword Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient Embeddings(2024)2 cited