🤖 Transformers - nmarshall · Scour

Applications of the Transformer Architecture in AI-Assisted English Reading Comprehension 🏗️AI Infrastructure

Paper page - Large Language Models Explore by Latent Distilling 🔍RAG

huggingface.co·5h

The Recurrent Transformer: Greater Effective Depth and Efficient Decoding (5 minute read) 🗣️Speech Synthesis

alphaxiv.org·1d

Temporal Language Models 📝Parser Combinators

calcifercomputing.com·2d·Hacker News

LayerBoost: Layer-Aware Attention Reduction for Efficient LLMs 💻Local LLMs

Associative-State Universal Transformers: Sparse Retrieval Meets Structured Recurrence 🔄Finite Automata

Fine-Grained Analysis of Shared Syntactic Mechanisms in Language Models 📝Parser Combinators

Investigation into In-Context Learning Capabilities of Transformers 🤖AI Inference

Dissociating Decodability and Causal Use in Bracket-Sequence Transformers 📝Parser Combinators

Barriers to Universal Reasoning With Transformers (And How to Overcome Them) 🎯Hindley-Milner

Training Transformers as a Universal Computer 🏗️AI Infrastructure

Estimating Tail Risks in Language Model Output Distributions 🏗️AI Infrastructure

Automating Categorization of Scientific Texts with In-Context Learning and Prompt-Chaining in Large Language Models 📝NLP

Adaptive ToR: Complexity-Aware Tree-Based Retrieval for Pareto-Optimal Multi-Intent NLU 📝Parser Combinators

The Recurrent Transformer: Greater Effective Depth and Efficient Decoding 📱Edge AI

G-Loss: Graph-Guided Fine-Tuning of Language Models 💻Local LLMs

The Structured Output Benchmark: A Multi-Source Benchmark for Evaluating Structured Output Quality in Large Language Models 🎙️Whisper

An Information-Geometric Framework for Stability Analysis of Large Language Models under Entropic Stress 📡Information Theory

Explainable AI in Speaker Recognition -- Making Latent Representations Understandable 🏗️AI Infrastructure

Large Language Models Explore by Latent Distilling 💻Local LLMs

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